Index

A

• accelerate.profiling
  • reference / There's more...
• adaptive histogram equalization
  • URL / There's more...
• adjacency matrix
  • about / Graphs
• Air resistance
  • URL / There's more...
• Altair / There's more...
  • plots, creating / Creating plots with Altair and the Vega-Lite specification, How to do it..., How it works..., There's more...
  • references / There's more...
• Anaconda
  • about / How to install Python
  • URL / How to install Python, Accelerating pure Python code with Numba and Just-In-Time compilation
• analog signals
  • about / Analog and digital signals
• array computations
  • accelerating, with NumExpr / Accelerating array computations with NumExpr, How to do it..., How it works...
• asynchronous parallel tasks
  • interacting, in IPython / Interacting with asynchronous parallel tasks in IPython, How to do it..., How it works...
• AsyncResult
  • references / There's more...
• audio filters
  • URL / There's more...
• audio signal processing
  • URL / References, There's more...
• augmented matrix / How to do it...
• AutoHotKey
  • URL / How to do it...
• Awesome Math
  • references / There's more...

B

• B-tree / There's more...
• bagging / Using a random forest to select important features for regression
• ball trees / How it works...
• band-pass filter / The low-, high-, and band-pass filters
• basin-hopping algorithm / How to do it..., How it works...
• Bayes' theorem
  • about / Bayes' theorem
• Bayesian methods
  • about / Frequentist and Bayesian methods, Getting started with Bayesian methods, Getting ready, How to do it...
  • Bayes' theorem / Bayes' theorem
  • posterior distribution, computation / Computation of the posterior distribution
  • Maximum a posteriori (MAP) / Maximum a posteriori estimation, There's more...
  • credible interval / Credible interval
  • conjugate distributions / Conjugate distributions
  • non-informative (objective) prior distributions / Non-informative (objective) prior distributions
• Bayesian model
  • applying, from a posterior distribution with MCMC / Fitting a Bayesian model by sampling from a posterior distribution with a Markov chain Monte Carlo method, How to do it..., How it works...
• benchmarking / Profiling your code easily with cProfile and IPython
• Bernoulli distribution
  • URL / How to do it...
• Bernoulli Naive Bayes classifier / How to do it...
• bias-variance dilemma / Overfitting, underfitting, and the bias-variance tradeoff
  • URL / Overfitting, underfitting, and the bias-variance tradeoff
• bias-variance tradeoff
  • URL / How it works...
  / Overfitting, underfitting, and the bias-variance tradeoff
• bifurcation diagram
  • plotting, of chaotic dynamical system / Plotting the bifurcation diagram of a chaotic dynamical system, How to do it...
• bifurcation diagrams
  • URL / There's more...
• Bifurcation theory
  • URL / There's more...
• Big O / How to do it...
• binder
  • URL / There's more...
• binomial distribution
  • about / How to do it...
• Birnbaum-Sanders distribution
  • about / How to do it...
  • URL / How to do it...
• Bisection method
  • reference / There's more…
• bisection method / How to do it...
• Bitbucket
  • URL / Getting ready
• bivariate method
  • about / Univariate and multivariate methods
• Blinn-Phong shading model
  • URL / How it works...
• block / How it works...
• blocking mode / How to do it...
• Bokeh
  • URL / Creating interactive web visualizations with Bokeh and HoloViews
  • interactive web visualizations, creating / Creating interactive web visualizations with Bokeh and HoloViews, How to do it..., There's more...
• Bookeh
  • references / There's more...
• Boolean propositional formula
  • searching, from truth table / Finding a Boolean propositional formula from a truth table, How to do it..., How it works...
  • URL / There's more...
• bootstrap aggregating / Using a random forest to select important features for regression
  • URL / There's more...
• boundary conditions / Differential equations
• bqplot / Discovering interactive visualization libraries in the Notebook
• branching
  • workflow / A typical workflow with Git branching, How to do it..., How it works...
  • references / There's more...
• Brent's method / How it works...
  • reference / There's more…
• broadcasting / How to do it...
• Brownian motion
  • simulating / Simulating a Brownian motion, How it works...
  • references / There's more...
• Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm / How to do it...
• Butterworth filter / The low-, high-, and band-pass filters

C

• calculus
  • URL / There's more..., There's more...
• Cameron Davidson-Pilon
  • URL / There's more...
• cardinal sine
  • URL / How to do it...
• Cartopy
  • geospatial data, manipulating / Manipulating geospatial data with Cartopy
  • URL / Getting ready
• cartopy
  • URL / How to do it...
  • geospatial data, manipulating / How to do it..., There's more...
• cascade
  • references / There's more...
• cascade classification API
  • URL / There's more...
• causal filters / Linear filters and convolutions
• cells / How it works...
• cellular automata
  • URL / There's more...
• cellular automaton / Types of dynamical systems
• Chaos theory
  • URL / There's more..., There's more...
• chaotic dynamical system / Plotting the bifurcation diagram of a chaotic dynamical system
  • bifurcation diagram, plotting / Plotting the bifurcation diagram of a chaotic dynamical system, How to do it...
• chi-squared test
  • used, for estimating correlation between two variables / Estimating the correlation between two variables with a contingency table and a chi-squared test, How to do it...
  • about / Contingency table and chi-squared test
  • references / There's more...
• Chinese Remainder Theorem / How it works...
  • references / There's more...
• choropleth map / Manipulating geospatial data with Cartopy
• chromatic scale
  • URL / There's more...
• chunks / There's more...
• chunk shape / There's more...
• classification / Supervised learning
• Classification and Regression Trees (CART) algorithm / How it works...
• C library
  • wrapping, in Python with ctypes / Wrapping a C library in Python with ctypes, How to do it..., How it works...
• client
  • about / Architecture of the Jupyter Notebook
• clustering
  • hidden structures, detecting in dataset / Detecting hidden structures in a dataset with clustering, How to do it..., How it works..., There's more...
  • URL / There's more...
• clusters / Detecting hidden structures in a dataset with clustering
• CMA-ES algorithm
  • URL / There's more...
• Codeship
  • URL / Unit testing and continuous integration
• column-major order / Why can't some arrays be reshaped without a copy?
• Comma-separated Values (CSV) / How to do it...
• CommonMark
  • URL / How to do it...
• complex systems
  • URL / There's more...
• components / Learning from data
• Comprehensive R Archive Network (CRAN)
  • URL / There's more...
• compressed sensing
  • about / Compressed sensing
  • references / Compressed sensing
  / How it works...
• Computational Fluid Dynamics
  • URL / References
• concurrent programming
  • about / CPython and concurrent programming
• conda
  • URL / How to do it...
• conditional probability distribution
  • about / Bayes' theorem
• connected-component labeling / How it works...
  • URL / There's more...
• connected components
  • URL / Problems in graph theory, There's more...
  • computing, in image / Computing connected components in an image, How to do it..., How it works..., There's more...
• constrained optimization / Local and global minima
• constrained optimization algorithm / How to do it...
• contiguous block / There's more...
• contingency table
  • used, for estimating correlation between two variables / Estimating the correlation between two variables with a contingency table and a chi-squared test, How to do it...
  • about / Contingency table and chi-squared test
  • URL / There's more...
• continuous functions / The objective function
• continuous integration / Unit testing and continuous integration
• continuous optimization
  • about / Introduction
• contrast
  • URL / There's more...
• Contrast Limited Adaptive Histogram Equalization (CLAHE) / How to do it...
• convex functions / The objective function
• convex optimization / The objective function
• convolution / Linear filters and convolutions
• Conway's Game of Life / There's more...
  • references / There's more...
• corner detection
  • URL / There's more...
• counting process / How to do it...
• Covariance Matrix Adaptation Evolution Strategy (CMA-ES) algorithm / How it works...
• coverage.py module
  • URL / Test coverage
• cProfile
  • used, for code profiling in IPython / Profiling your code easily with cProfile and IPython, How to do it..., How it works..., There's more...
  • about / Profiling your code easily with cProfile and IPython
  • reference / There's more...
• CPython
  • about / CPython and concurrent programming
• credible intervals
  • about / Credible interval
  • URL / Credible interval
• cross-validation / Cross-validation and grid search
  • references / There's more...
• ctypes
  • C library, wrapping in Python / Wrapping a C library in Python with ctypes, How to do it..., How it works...
  • URL / There's more...
• CUDA
  • massively parallel code, writing for NVIDIA graphics cards / Writing massively parallel code for NVIDIA graphics cards (GPUs) with CUDA, How to do it..., How it works...
  • references / There's more...
• CUDA cores / How it works...
• Cumulative Distribution Function (CDF) / How to do it...
• curve fitting / How to do it...
• custom Jupyter Notebook widgets
  • creating, in Python / Creating custom Jupyter Notebook widgets in Python, HTML, and JavaScript, How to do it...
  • creating, in HTML / Creating custom Jupyter Notebook widgets in Python, HTML, and JavaScript, How to do it...
  • creating, in JavaScript / Creating custom Jupyter Notebook widgets in Python, HTML, and JavaScript, How to do it...
• custom magic commands
  • IPython extension, creating / Creating an IPython extension with custom magic commands, How to do it..., How it works...
• custom widget
  • URL / There's more...
  • URK / There's more...
• Cython
  • URL / Compiler-related installation instructions
  • Python code, accelerating / Accelerating Python code with Cython, How to do it..., How it works...
  • references / There's more..., There's more...
  • code, optimizing / Optimizing Cython code by writing less Python and more C, How to do it..., How it works...
  • used, for releasing GIL / Releasing the GIL to take advantage of multi-core processors with Cython and OpenMP, Getting ready, How it works...

D

• D3.js
  • URL / Visualizing a NetworkX graph in the Notebook with D3.js
  • NetworkX graph, visualizing in Notebook / Visualizing a NetworkX graph in the Notebook with D3.js, How to do it..., There's more...
• Dask
  • URL / How to do it...
  • out-of-core computations, performing on large arrays / Performing out-of-core computations on large arrays with Dask, How to do it..., There's more...
  • references / There's more...
• data buffer / Why are NumPy arrays efficient?
• data dimensionality
  • reducing, with principal component analysis / Reducing the dimensionality of a dataset with a principal component analysis, How to do it..., How it works...
• data manipulation
  • references / There's more...
• data normalization / Feature selection and feature extraction
• dataset
  • exploring, with pandas / Exploring a dataset with pandas and Matplotlib, How to do it..., There's more...
  • exploring, with Matplotlib / Exploring a dataset with pandas and Matplotlib, How to do it..., There's more...
• datasets / How it works...
• Datashader
  • URL / There's more...
• data type (dtype) / How it works...
• data visualization / Reducing the dimensionality of a dataset with a principal component analysis
• decision tree learning
  • URL / There's more...
• decision trees / Using a random forest to select important features for regression
• decompositions
  • URL / There's more...
• deep learning / Feature selection and feature extraction
  • references / Machine learning references
• defensive programming / How to do it...
• Delaunay triangulation
  • URL / How it works...
• dependencies
  • functional dependency / There's more...
  • graph dependency / There's more...
• design patterns / How to do it...
• deterministic algorithm / Deterministic and stochastic algorithms
• dichotomy method / How to do it...
• differentiable functions / The objective function
• digital filters
  • applying, to speech sounds / Applying digital filters to speech sounds, Getting ready, How to do it, How it works...
• digital signal
  • linear filter, applying / Applying a linear filter to a digital signal, How to do it...
  • about / How it works...
• digital signals
  • about / Analog and digital signals
  • sampling rate / Analog and digital signals
  • resolution / Analog and digital signals
• Dijkstra's algorithm / How it works...
  • URL / There's more...
• dilation / How it works...
• dill
  • URL / How to do it...
• dimensionality / Learning from data
• Direct Acyclic Graph (DAG) / How it works...
• Directed Acyclic Graph (DAG) / How to do it...
  • references / There's more...
• direct interface / How it works...
• discrete-time dynamical system / Types of dynamical systems
• discrete-time Markov chain
  • simulating / Simulating a discrete-time Markov chain, How to do it..., How it works...
• Discrete Fourier Transform (DFT) / The discrete Fourier transform
• discrete optimization
  • about / Introduction
• distributed version control system
  • about / Learning the basics of the distributed version control system Git, How to do it..., How it works..., There's more...
• Docker
  • URL / How to do it...
• dot-com bubble burst
  • about / How to do it...
• dynamical systems
  • about / Introduction
  • types / Types of dynamical systems
  • differential equations / Differential equations
  • references / References
  • URL / There's more...
• Dynamic Random Access Memory (DRAM) / How it works...

E

• Eclipse/PyDev / Integrated Development Environments
• elastic potential energy / How it works...
  • URL / There's more...
• elementary cellular automata
  • URL / There's more...
• elementary cellular automaton
  • simulating / Simulating an elementary cellular automaton, How to do it..., How it works...
• embarrassingly parallel
  • URL / How to do it...
• empirical distribution function / How to do it...
• ensemble learning / Using a random forest to select important features for regression
  • URL / There's more...
• equal temperament
  • URL / There's more...
• equilibrium points / How it works...
  • URL / There's more...
• erosion / How it works...
• estimation
  • about / Exploration, inference, decision, prediction
• Euler-Maruyama method / Simulating a stochastic differential equation
  • URL / There's more...
• Eulerian paths
  • URL / Problems in graph theory
• Euler method / How it works...
  • URL / There's more...
• expectation-maximization algorithm / How it works...
  • URL / There's more...
• exploratory data analysis
  • using, in Jupyter Notebook / Getting started with exploratory data analysis in the Jupyter Notebook, How to do it...
  / How it works...
• exploratory methods
  • about / Exploration, inference, decision, prediction

F

• f-strings / How to do it...
• Fast Fourier Transform (FFT)
  • used, for analyzing frequency components / Analyzing the frequency components of a signal with a Fast Fourier Transform, How to do it...
  • discrete Fourier transform / The discrete Fourier transform
  • Inverse Fourier Transform / Inverse Fourier transform, There's more...
  • references / There's more...
• feature / Learning from data
• feature extraction / Feature selection and feature extraction
• feature scaling / Feature selection and feature extraction
• feature selection / Feature selection and feature extraction
  • URL / Feature selection and feature extraction
• filters
  • applying, on image / Applying filters on an image, How it works..., How it works...
• Finite Impulse Response (FIR) / The FIR and IIR filters
• FIR filter / How to do it...
• FitzHugh-Nagumo equation / Simulating a partial differential equation — reaction-diffusion systems and Turing patterns
• FitzHugh-Nagumo system
  • URL / There's more...
• fixtures / How it works...
• Flake8
  • URL / How to do it...
• flight routes
  • drawing, with NetworkX / Drawing flight routes with NetworkX, How to do it...
• flood-fill algorithm / How it works...
  • URL / There's more...
• fluid dynamics / Differential equations
• Fokker-Planck equation / How it works...
  • URL / There's more...
• Force-directed graph drawing
  • URL / There's more...
• forking / There's more...
• Fourier transform
  • about / The Nyquist–Shannon sampling theorem
• frequentist and Bayesian methods
  • about / Frequentist and Bayesian methods
• frequentist methods
  • about / Frequentist and Bayesian methods
  • URL / Frequentist and Bayesian methods
• Fruchterman-Reingold force-directed algorithm / There's more...
• fundamental frequency / How it works...

G

• Gaussian filter / How it works...
  • URL / There's more...
• Gaussian kernel / How it works...
• General Purpose Programming on Graphics Processing Units (GPGPU) / Writing massively parallel code for NVIDIA graphics cards (GPUs) with CUDA
• geodetic coordinate system / How to do it...
• geographical distances
  • references / There's more...
• Geographical information systems
  • using, in Python / Geographical information systems in Python
• Geographic Information Systems (GIS)
  • about / Introduction
• geometry
  • using, in Python / Geometry in Python
  • references / References
• geospatial data
  • manipulating, with Cartopy / Manipulating geospatial data with Cartopy, How to do it..., There's more...
• Git
  • references / There's more...
• git-flow
  • references / There's more...
• GitHub
  • URL / Getting ready
• GitLab
  • URL / Getting ready
• Git Large File Storage (Git LFS)
  • URL / How it works...
• Global Interpreter Lock (GIL)
  • references / CPython and concurrent programming
• global minimum / Local and global minima
• gradient
  • URL / There's more...
• gradient descent / How it works...
• graph
  • about / Graphs
• graph, problems
  • graph traversal / Problems in graph theory
  • graph coloring / Problems in graph theory
  • connected components / Problems in graph theory
  • Hamiltonian paths / Problems in graph theory
  • Eulerian paths / Problems in graph theory
  • traveling salesman problem / Problems in graph theory
• graph coloring
  • URL / Problems in graph theory
• Graph drawing
  • URL / There's more...
• Graphics Processing Units (GPUs) / Introduction
  • about / Writing massively parallel code for NVIDIA graphics cards (GPUs) with CUDA
• graphs
  • about / Introduction, Graphs
  • random graphs / Random graphs
  • using, in Python / Graphs in Python
  • references / References
  • manipulating, with NetworkX / Manipulating and visualizing graphs with NetworkX, How to do it..., There's more...
  • visualizing, with NetworkX / Manipulating and visualizing graphs with NetworkX, How to do it..., There's more...
• graph traversal
  • URL / Problems in graph theory
• Graphviz
  • URL / How to do it...
• gravitational force / How it works...
• grayscale image / Images
• great-circle distance / How it works...
• grid / How it works...
• grid search / Cross-validation and grid search
  • URL / There's more...
• Gross Domestic Product (GDP) / Manipulating geospatial data with Cartopy
• groups / How it works..., Detecting hidden structures in a dataset with clustering

H

• 44100 Hz sampling rate
  • URL / References
• h5py
  • reference / There's more...
• Haar cascades library
  • URL / There's more...
• Hamiltonian paths
  • URL / Problems in graph theory
• handwritten digit recognition / Supervised learning
• Hartman-Grobman theorem / How it works...
• HDF5 chunking
  • reference / There's more...
• heat equation / How it works...
• Hessian / How it works...
• Hierarchical Data Format (HDF5)
  • used, for manipulating large arrays / Manipulating large arrays with HDF5, How it works..., There's more...
  • limitations, reference / There's more...
• high-pass filter / The low-, high-, and band-pass filters
• histogram equalization
  • URL / There's more...
• holding times / How it works...
• HoloViews
  • interactive web visualizations, creating / Creating interactive web visualizations with Bokeh and HoloViews, How to do it..., There's more...
• Hooke's law
  • URL / There's more...
• Hyper-Threading Technology (HTT) / How to do it...
• hyperbolic / How it works...

I

• image
  • filters, applying / How it works..., How it works...
  • segmenting / Segmenting an image, How to do it..., How it works...
  • points of interest, searching / Finding points of interest in an image, How to do it..., How it works...
  • faces, detecting with OpenCV / Detecting faces in an image with OpenCV, How to do it..., How it works...
• image data, transforming
  • URL / There's more...
• image denoising / How it works...
• image exposure
  • manipulating / Manipulating the exposure of an image, Getting ready, How to do it..., How it works...
• image histogram
  • URL / There's more...
• image processing
  • URL / References, There's more..., There's more...
• images / Images
• image segmentation
  • URL / There's more...
• in-place operation
  • and implicit-copy operation, differences / What is the difference between in-place and implicit-copy operations?
• independent variables / Types of dynamical systems
• Infinite Impulse Response (IIR) / The FIR and IIR filters
• instance-based learning / How it works...
  • URL / There's more...
• Integrated Development Environments (IDEs) / Efficient interactive computing workflows with IPython
• Intel Math Kernel Library (MKL) / Why are NumPy arrays efficient?
• intensity / Images
• interactive computing / Introduction
• interactive computing workflow
  • with IPython / Efficient interactive computing workflows with IPython
• InteractiveShell class / The InteractiveShell class
• interactive visualization libraries
  • discovering, in Notebook / Discovering interactive visualization libraries in the Notebook, How to do it...
  • references / There's more
• interactive web visualizations
  • creating, with Bokeh / Creating interactive web visualizations with Bokeh and HoloViews, How to do it..., There's more...
  • creating, with HoloViews / Creating interactive web visualizations with Bokeh and HoloViews, How to do it..., There's more...
• intermediate value theorem / How it works...
  • reference / There's more…
• Inverse Discrete Fourier Transform / Inverse Fourier transform
• Inverse Fast Fourier Transform / Inverse Fourier transform
• ipyleaflet / Getting started
• ipymd module
  • URL / The Jupyter Notebook
• ipyparallel / How to do it..., Distributing Python code across multiple cores with IPython
  • references / References
• IPython
  • about / What is IPython?, Introducing IPython and the Jupyter Notebook, How to do it..., There's more...
  • interactive computing workflows / Efficient interactive computing workflows with IPython
  • terminal / The IPython terminal
  • text editor / IPython and text editor
  • URL / IPython and text editor
  • Jupyter Notebook / The Jupyter Notebook
  • Integrated Development Environments (IDEs) / Integrated Development Environments
  • IDEs, references / There's more...
  • code, debugging / Debugging code with IPython, How to do it..., There's more...
  • post-mortem mode / The post-mortem mode
  • debugging / Step-by-step debugging
  • command time, evaluating / Evaluating the time taken by a command in IPython, How it works...
  • cProfile, used, for code profiling / Profiling your code easily with cProfile and IPython, How to do it..., How it works..., There's more...
  • Python code, distributing across multiple cores / Distributing Python code across multiple cores with IPython, How to do it..., How it works..., There's more...
  • asynchronous parallel tasks, interacting / Interacting with asynchronous parallel tasks in IPython, How to do it..., How it works...
• IPython's configuration system
  • mastering / Mastering IPython's configuration system, How to do it..., How it works...
• IPython Blocks
  • used, as programming tutorial in Notebook / Teaching programming in the Notebook with IPython Blocks, How to do it...
  • URL / Teaching programming in the Notebook with IPython Blocks
• IPython configuration system
  • user profile / How it works...
  • configuration object / How it works...
  • HasTraits class / How it works...
  • Configurable class / How it works..., Configurables
  • configuration file / How it works...
  • Magics class / Magics
  • references / There's more...
• IPython extension
  • creating, with custom magic commands / Creating an IPython extension with custom magic commands, How to do it..., How it works...
  • InteractiveShell class / The InteractiveShell class
  • loading / Loading an extension
  • references / There's more...
• IPython Notebook
  • about / What is IPython?
• ipyvolume / Discovering interactive visualization libraries in the Notebook
• ipywidgets
  • about / Mastering widgets in the Jupyter Notebook, How to do it..., There's more...
  • URL / There's more...
• Iris dataset
  • URL / There's more...
• Iris flower dataset
  • URL / There's more...
• IRkernel
  • URL / Analyzing data with the R programming language in the Jupyter Notebook
• iterated functions
  • URL / There's more...

J

• Jacobian / How to do it...
• Jacobian matrix / How it works...
• JavaScript Object Notation (JSON)
  • about / The Notebook ecosystem
• Jeffreys prior
  • URL / Non-informative (objective) prior distributions
• Jinja2
  • URL / How it works...
• Joblib
  • URL / How to do it...
• Julia
  • URL / Trying the Julia programming language in the Jupyter Notebook
  • using, in Jupyter Notebook / Trying the Julia programming language in the Jupyter Notebook, How to do it..., How it works...
  • references / There's more...
• Jupyter
  • about / What is Jupyter?
  • kernel, creating / Creating a simple kernel for Jupyter, How to do it..., How it works...
• JupyterHub
  • about / JupyterHub
  • URL / JupyterHub
• JupyterLab / The Jupyter Notebook
  • about / The Notebook ecosystem, Introducing JupyterLab, Getting ready, How to do it..., There's more...
  • references / There's more...
• Jupyter Notebook
  • about / Introducing IPython and the Jupyter Notebook, How to do it..., There's more...
  • references / There's more..., There's more...
  • exploratory data analysis / Getting started with exploratory data analysis in the Jupyter Notebook, How to do it..., How it works...
  • architecture / Architecture of the Jupyter Notebook
  • clients, connecting to kernel / Connecting multiple clients to one kernel
  • JupyterHub / JupyterHub
  • programming tutorial, with IPython Blocks / Teaching programming in the Notebook with IPython Blocks, How to do it...
  • converting, with nbconvert / Converting a Jupyter notebook to other formats with nbconvert, How to do it..., How it works..., There's more...
  • widgets / Mastering widgets in the Jupyter Notebook, How to do it..., There's more...
  • configuring / Configuring the Jupyter Notebook, How to do it...
  • Julia, using / Trying the Julia programming language in the Jupyter Notebook, How to do it..., How it works...
  • data, analyzing with R / Analyzing data with the R programming language in the Jupyter Notebook, How to do it..., How it works...
• Jupyter notebook
  • security / Security in notebooks
  • references / References
• Just-In-Time (JIT) / Introduction
• Just-In-Time compilation
  • Python code, accelerating / Accelerating pure Python code with Numba and Just-In-Time compilation, How to do it..., How it works...

K

• K-D trees / How it works...
• K-means clustering algorithm
  • URL / There's more...
• K-nearest neighbors (K-NN) classifier
  • handwritten digits, recognizing / Learning to recognize handwritten digits with a K-nearest neighbors classifier, How to do it..., How it works...
• K-NN algorithm
  • references / There's more...
• Kaggle
  • references / Predicting who will survive on the Titanic with logistic regression
  • URL / Learning from text – Naive Bayes for Natural Language Processing
• kernel
  • creating, for Jupyter / Creating a simple kernel for Jupyter, How to do it..., How it works...
  • references / There's more...
  • about / Architecture of the Jupyter Notebook
  • clients, connecting / Connecting multiple clients to one kernel
  / How it works...
• Kernel Density Estimation (KDE) / How to do it..., Estimating a probability distribution nonparametrically with a kernel density estimation
  • URL / How it works...
• Kolmogorov-Smirnov test / How to do it...
  • URL / There's more...

L

• L-BFGS-B algorithm
  • URL / There's more...
• Langevin equation / Simulating a stochastic differential equation
  • URL / There's more...
• Laplacian matrix / There's more...
  • URL / There's more...
• large arrays
  • manipulating, with Hierarchical Data Format (HDF5) / Manipulating large arrays with HDF5, How to do it..., There's more...
• LaTeX / LaTeX
  • URL / Getting ready
  • references / LaTeX
• least squares
  • references / There's more...
• least squares method
  • references / There's more...
• Leave-one-out cross-validation (LOOCV) / Cross-validation and grid search
• left singular vectors / How it works...
• Levenberg-Marquardt algorithm / How it works...
• linear algebra
  • references / There's more...
• linear combination / How it works...
• linear filter
  • applying, to digital signal / Applying a linear filter to a digital signal, How to do it...
  • about / What are linear filters?
  • convolution / Linear filters and convolutions
  • FIR / The FIR and IIR filters
  • IIR filters / The FIR and IIR filters
  • filters, using in frequency domain / Filters in the frequency domain
  • low-pass filter / The low-, high-, and band-pass filters
  • high-pass filter / The low-, high-, and band-pass filters
  • band-pass filter / The low-, high-, and band-pass filters
  • references / There's more...
• Linear Time-Invariant (LTI)
  • about / What are linear filters?
• line_profiler
  • used, for line-by-line code profiling / Profiling your code line-by-line with line_profiler, How do to it..., There's more...
  • reference / There's more...
• Lloyd's algorithm / How it works...
• load-balanced interface / How it works...
• locality of reference / Why are NumPy arrays efficient?
• local minimum / Local and global minima
• logic lectures
  • URL / There's more...
• logic module
  • URL / There's more...
• logistic map / Plotting the bifurcation diagram of a chaotic dynamical system
  • URL / There's more...
• logistic regression
  • using, for prediction / Predicting who will survive on the Titanic with logistic regression, How to do it..., How it works...
  • references / There's more...
• loss function
  • about / How to do it...
  / Ordinary Least Squares regression
• Lotka-Volterra (predator-prey) equations
  • implementing / Analyzing a nonlinear differential system — Lotka-Volterra (predator-prey) equations, How to do it..., How it works...
• low-pass filter / The low-, high-, and band-pass filters
• Low Level Virtual Machine (LLVM) / How it works...
• Lyapunov exponent / Plotting the bifurcation diagram of a chaotic dynamical system
  • URL / There's more...
• L² norm / Ordinary Least Squares regression
• Lévi function / How to do it...

M

• machine learning / Introduction
  • references / Machine learning references
• maps
  • references / References
• Markov chain Monte Carlo (MCMC) method / Fitting a Bayesian model by sampling from a posterior distribution with a Markov chain Monte Carlo method
  • Bayesian model, applying from posterior distribution / Fitting a Bayesian model by sampling from a posterior distribution with a Markov chain Monte Carlo method, How to do it..., How it works...
  • URL / There's more...
• Markov chains / Introduction
  • references / There's more...
• Markov property / Introduction
  • URL / References
• mathematical function
  • root, finding / Finding the root of a mathematical function, How to do it..., How it works...
  • references, for root finding / There's more…
  • minimizing / Minimizing a mathematical function, How to do it..., How it works...
• mathematical morphology
  • URL / There's more...
• mathematical morphology techniques / How it works...
• mathematical optimization
  • about / Introduction
  • objective function / The objective function
  • local minima / Local and global minima
  • global minima / Local and global minima
  • unconstrained optimization / Constrained and unconstrained optimization
  • constrained optimization / Constrained and unconstrained optimization
  • deterministic algorithm / Deterministic and stochastic algorithms
  • stochastic algorithm / Deterministic and stochastic algorithms
  • references / References
  • URL / There's more...
• MathJax / LaTeX
• Matplotlib
  • about / What is the SciPy ecosystem?
  • URL / What's new in the SciPy ecosystem?
  • dataset, exploring / Exploring a dataset with pandas and Matplotlib, How to do it..., There's more...
• Matplotlib styles
  • using / Using Matplotlib styles, How to do it...
  • references / There's more...
• matrix / How it works...
• matrix documentation
  • URL / There's more...
• Maximum a posteriori (MAP) / Maximum a posteriori estimation, There's more...
• maximum likelihood method
  • data, probability distribution applying / Fitting a probability distribution to data with the maximum likelihood method, How to do it..., How it works...
  • URL / There's more...
• memmap
  • reference / There's more...
• memory mapping
  • used, for processing NumPy arrays / Processing large NumPy arrays with memory mapping, How it works...
• memory profiling
  • memory_profiler, using / Profiling the memory usage of your code with memory_profiler, How to do it..., There's more...
• memory_profiler
  • used, for memory profiling / Profiling the memory usage of your code with memory_profiler, How to do it..., There's more...
  • reference / There's more...
• Metaheuristics
  • URL / There's more...
• Metropolis-Hastings algorithm / Fitting a Bayesian model by sampling from a posterior distribution with a Markov chain Monte Carlo method, How it works...
  • URL / There's more...
• Microsoft Visual Studio
  • URL / Compiler-related installation instructions
• Milstein method
  • URL / There's more...
• model evaluation
  • URL / Model selection
• model selection
  • about / Model selection
  • URL / Model selection
• Monte Carlo methods
  • URL / There's more...
• multidimensional array
  • using, in NumPy for array computations / Introducing the multidimensional array in NumPy for fast array computations, How to do it..., How it works..., There's more...
• multiprocessing module / Distributing Python code across multiple cores with IPython
• multivariate method
  • about / Univariate and multivariate methods

N

• Naive Bayes
  • for Natural Language Processing / Learning from text – Naive Bayes for Natural Language Processing
• Naive Bayes classifier
  • references / There's more...
• Natural Earth
  • URL / Manipulating geospatial data with Cartopy
• natural language processing
  • references / There's more...
• Navier-Stokes equations / Differential equations
  • URL / References
• nbconvert
  • URL / There's more..., There's more...
  • Jupyter notebook, converting / How to do it..., How it works..., There's more...
• nbconvert
  • Jupyter notebook, converting / Converting a Jupyter notebook to other formats with nbconvert
  • URL / Converting a Jupyter notebook to other formats with nbconvert
• nbformat
  • URL / Converting a Jupyter notebook to other formats with nbconvert
• nbviewer
  • URL / There's more..., There's more...
• NetworkX
  • graphs, manipulating / Getting ready, How to do it..., There's more...
  • graphs, visualizing / Getting ready, How to do it..., There's more...
  • flight routes, drawing / Drawing flight routes with NetworkX, How to do it...
• NetworkX graph
  • visualizing, in Notebook with D3.js / Visualizing a NetworkX graph in the Notebook with D3.js, How to do it..., There's more...
  • references / There's more...
• Neumann boundary conditions
  • URL / There's more...
• Newton's laws of motion
  • URL / There's more...
• Newton's method / How it works...
  • reference / There's more…
  • URL / There's more...
• nodes
  • about / Introduction
• noise reduction
  • URL / There's more...
• non-contiguous / How to do it...
• nonlinear kernels / How to do it...
• nonlinear least squares
  • function, fitting to data / Fitting a function to data with nonlinear least squares, How to do it..., How it works...
  • references / How it works...
• nonlinear least squares curve fitting / Fitting a function to data with nonlinear least squares
• nonparametric estimation / Estimating a probability distribution nonparametrically with a kernel density estimation
• nonparametric model
  • about / Parametric and nonparametric inference methods
• Notebook
  • sound synthesizer, creating / Creating a sound synthesizer in the Notebook, How to do it..., How it works...
• NPY file format
  • reference / There's more...
• nteract
  • about / There's more...
• null hypothesis
  • about / How to do it...
• Numba / Introduction
  • URL / Accelerating pure Python code with Numba and Just-In-Time compilation
  • Python code, accelerating / Accelerating pure Python code with Numba and Just-In-Time compilation, How to do it..., How it works...
  • references / There's more...
• number-theory module
  • references / There's more...
• Numerical Tours
  • URL / References
• NumExpr / Introduction
  • array computations, accelerating / Accelerating array computations with NumExpr, How to do it..., How it works...
  • references / How it works...
• NumPy
  • about / What's new in the SciPy ecosystem?
  • URL / What's new in the SciPy ecosystem?
  • multidimensional array, using for array computations / Introducing the multidimensional array in NumPy for fast array computations, How to do it..., How it works..., There's more...
  • references / There's more...
  • unnecessary array copies, avoiding / Understanding the internals of NumPy to avoid unnecessary array copying, Getting ready, How to do it...
  • broadcasting rules / What are NumPy broadcasting rules?
  • stride tricks, using / Using stride tricks with NumPy, How to do it..., How it works...
• NumPy arrays
  • efficiency / Why are NumPy arrays efficient?
  • reshaping, without copy / Why can't some arrays be reshaped without a copy?
  • processing, with memory mapping / Processing large NumPy arrays with memory mapping
  • about / How it works...
• NumPy broadcasting rules
  • about / What are NumPy broadcasting rules?
  • references / There's more...
• NVIDIA graphics cards (GPUs)
  • massively parallel code, writing with CUDA / Writing massively parallel code for NVIDIA graphics cards (GPUs) with CUDA, How to do it..., How it works...
• Nyquist-Shannon sampling theorem
  • about / The Nyquist–Shannon sampling theorem
• Nyquist criterion
  • about / The Nyquist–Shannon sampling theorem

O

• objective function / The objective function
• observation / Learning from data
• ODEPACK package
  • URL / There's more...
• offset / Getting ready
• Online Python Tutor
  • reference / There's more...
• OpenCL / Writing massively parallel code for NVIDIA graphics cards (GPUs) with CUDA
• OpenCV
  • URL / Introduction
• OpenCV (Open Computer Vision)
  • used, for detecting faces in image / Detecting faces in an image with OpenCV, How to do it..., How it works...
• OpenFlights
  • URL / Drawing flight routes with NetworkX
• OpenMP
  • used, for releasing GIL / Releasing the GIL to take advantage of multi-core processors with Cython and OpenMP, Getting ready, How it works...
• ordinary differential equations
  • URL / There's more...
• Ordinary Differential Equations (ODEs) / Types of dynamical systems
  • simulating, with SciPy / Simulating an ordinary differential equation with SciPy, How to do it..., How it works...
  • references / There's more...
• Ordinary Least Squares (OLS) regression / Ordinary Least Squares regression
• Ornstein-Uhlenbeck process / Simulating a stochastic differential equation
• orthodromic distance / How it works...
• Otsu's method / How to do it...
  • URL / There's more...
• out-of-core computations / Processing large NumPy arrays with memory mapping
• outer product / How to do it...
• overfitting / Supervised learning, Overfitting, underfitting, and the bias-variance tradeoff
  • URL / Overfitting, underfitting, and the bias-variance tradeoff
  • about / How to do it...

P

• pandas
  • about / What is the SciPy ecosystem?
  • dataset, exploring / Exploring a dataset with pandas and Matplotlib, How to do it..., There's more...
  • references / There's more...
• pandas 0.21
  • URL / What's new in the SciPy ecosystem?
• pandoc
  • URL / Getting ready
• parameter vector / Ordinary Least Squares regression
• parametric estimation method / Estimating a probability distribution nonparametrically with a kernel density estimation
• parametric method
  • about / Parametric and nonparametric inference methods
• partial derivatives / Types of dynamical systems
• Partial Differential Equations (PDEs) / Types of dynamical systems
  • simulating / Simulating a partial differential equation — reaction-diffusion systems and Turing patterns, How to do it..., How it works...
  • references / There's more...
• partitions / Supervised learning
• PCA
  • URL / There's more...
• Pearson correlation coefficient
  • about / Pearson's correlation coefficient
  • URL / Pearson's correlation coefficient
• physical system
  • equilibrium state, finding by potential energy minimization / Finding the equilibrium state of a physical system by minimizing its potential energy, How to do it..., How it works..., There's more...
• pip / How to install Python
• pipes
  • about / How to do it...
• plate carrée / How to do it...
• Plotly
  • URL / There's more...
• podoc module
  • URL / The Jupyter Notebook
• point process / Simulating a Poisson process
• point processes / Introduction
• points of interest
  • searching, of image / Finding points of interest in an image, How to do it..., How it works...
• Poisson process
  • about / How to do it...
  • URL / How to do it...
  • simulating / Simulating a Poisson process, How to do it..., How it works...
  • references / There's more...
• polynomial interpolation
  • with linear regression / Polynomial interpolation with linear regression
• potential energy
  • URL / There's more...
• Power Spectral Density
  • about / How to do it...
• prediction
  • about / Exploration, inference, decision, prediction
• prime-counting function / How to do it...
• prime number theorem / How to do it...
• principal component / How it works...
• principal component analysis
  • data dimensionality, reducing / Reducing the dimensionality of a dataset with a principal component analysis, How to do it..., How it works...
• Principal Component Analysis (PCA) / Reducing the dimensionality of a dataset with a principal component analysis
• principle of minimum energy
  • URL / There's more...
• principle of minimum total potential energy / How it works...
• prior probability distribution
  • about / How to do it...
• probabilistic model
  • about / Parametric and nonparametric inference methods
• probability distribution
  • applying, to data with maximum likelihood method / Fitting a probability distribution to data with the maximum likelihood method, How to do it..., How it works...
• probability distribution nonparametrically
  • estimating, with kernel density estimation / Estimating a probability distribution nonparametrically with a kernel density estimation, How to do it..., How it works...
• Probability Mass Function (PMF)
  • about / How to do it...
• probit model
  • URL / Supervised learning
• profile / Introduction
• profiling / Profiling your code easily with cProfile and IPython
• pstats
  • reference / There's more...
• pull request / There's more...
• pure tone / How it works...
• py.test
  • unit tests, writing / Writing unit tests with pytest, How to do it..., How it works...
• PyCall / There's more...
• PyCharm / Integrated Development Environments
• pydot / How it works...
• pyjulia / There's more...
• Pylint
  • URL / How to do it...
• PyMC3
  • references / Fitting a Bayesian model by sampling from a posterior distribution with a Markov chain Monte Carlo method
• PyPy
  • URL / Introduction
• PyTables optimization guide
  • reference / There's more...
• Python
  • about / What is Python?
  • installing / How to install Python
  • references / References, Introduction
  • profiling tools, reference / There's more...
  • compilers, using / Compiler-related installation instructions
  • C library, wrapping with ctypes / Wrapping a C library in Python with ctypes, How to do it..., How it works...
• Python 3
  • features, using / Using the latest features of Python 3, How to do it..., There's more...
  • references / There's more...
  • URL / There's more...
• Python code
  • writing / Writing high-quality Python code, How to do it...
  • references / There's more...
  • improving / Using Python to write faster code, How to do it...
  • accelerating, with Numba / Accelerating pure Python code with Numba and Just-In-Time compilation, How to do it..., How it works...
  • accelerating, with Just-In-Time compilation / Accelerating pure Python code with Numba and Just-In-Time compilation, How to do it..., How it works...
  • accelerating, with Cython / Accelerating Python code with Cython, How to do it..., How it works...
  • distributing, across multiple cores with IPython / Distributing Python code across multiple cores with IPython, How to do it..., How it works..., There's more...
• Python debuggers
  • URL / There's more...
• Python Enhancement Proposal number 8 (PEP8)
  • URL / How to do it...
• Python Package Index (PyPI)
  • URL / How to install Python
• Python Tools for Visual Studio (PTVS) / Integrated Development Environments
• pythreejs / Discovering interactive visualization libraries in the Notebook

Q

• Quasi-Newton methods / How it works...
  • URL / There's more...
• Quine-McCluskey algorithm / How it works...
  • URL / There's more...

R

• R
  • URL / Analyzing data with the R programming language in the Jupyter Notebook
  • data, analyzing in Jupyter Notebook / Analyzing data with the R programming language in the Jupyter Notebook, How to do it..., How it works...
  • references / There's more...
• Rackspace
  • URL / There's more...
• Radial Basis Function (RBF) / How to do it...
• Random Access Memory (RAM) / Why are NumPy arrays efficient?
• random forest
  • about / Using a random forest to select important features for regression
  • used, for selecting features for regression / Using a random forest to select important features for regression, How to do it..., How it works...
• RandomForestRegressor
  • URL, for API / There's more...
• random forests
  • URL / There's more...
• random graphs / Random graphs
• random subspace method / How it works...
  • URL / There's more...
• random variable
  • about / How to do it...
• Ray tracing / Optimizing Cython code by writing less Python and more C
  • URL / How it works...
• reachability relation / How it works...
• reaction-diffusion system / Simulating a partial differential equation — reaction-diffusion systems and Turing patterns
• reaction-diffusion systems
  • references / There's more...
  • URL / There's more...
• Read-Eval-Print Loop (REPL) / Efficient interactive computing workflows with IPython
• Read-Evaluate-Print Loop (REPL)
  • about / Architecture of the Jupyter Notebook
• real-valued functions
  • analyzing / Analyzing real-valued functions, How to do it...
• real analysis
  • references / There's more...
• rebasing / How it works...
• red, green, and blue (RGB) / Images
• regions / How it works...
• regression / Supervised learning
• regression analysis
  • references / There's more...
• regularization
  • URL / Overfitting, underfitting, and the bias-variance tradeoff
• regularization term
  • about / How to do it...
• reproducible interactive computing experiments
  • conducting / Ten tips for conducting reproducible interactive computing experiments, How to do it..., How it works..., There's more...
  • references / There's more...
• RequireJS
  • URK / There's more...
• reStructuredText (reST)
  • URL / How to do it...
• ridge regression
  • about / How to do it...
  / Ridge regression
• RISE
  • URL / There's more...
• robust model / Overfitting, underfitting, and the bias-variance tradeoff
• Rodeo / Integrated Development Environments
• rolling average algorithm
  • implementing, with stride tricks / Implementing an efficient rolling average algorithm with stride tricks, How to do it...
  • about / Implementing an efficient rolling average algorithm with stride tricks
• rolling mean / How to do it...
• route planner
  • creating, for road network / Creating a route planner for a road network, How to do it..., How it works...
• row-major order / Why can't some arrays be reshaped without a copy?
• rpy2
  • URL / Getting ready
• Rule 110
  • URL / There's more...
• Rule 110 automaton / How it works...
• rule of thumb / How it works...

S

• Sage / Introduction
  • URL / Getting started with Sage
  • about / Getting started with Sage, How to do it..., There's more...
  • references / Getting ready, There's more...
• sample / Learning from data
• Scalable Vector Graphics (SVG)
  • about / How to do it...
• scientific Python
  • references / References
• scikit-learn / Introduction
  • URL / Feature selection and feature extraction, Getting started with scikit-learn, How it works...
  • about / Getting started with scikit-learn, How to do it..., How it works...
  • API / scikit-learn API
  • Ordinary Least Squares regression / Ordinary Least Squares regression
  • polynomial interpolation, with linear regression / Polynomial interpolation with linear regression
  • ridge regression / Ridge regression
  • cross-validation / Cross-validation and grid search
  • grid search / Cross-validation and grid search
  • references / There's more...
  • text data, handling / Learning from text – Naive Bayes for Natural Language Processing, How to do it..., How it works...
• SciPy
  • URL / What is the SciPy ecosystem?
  • ODEs, simulating / Simulating an ordinary differential equation with SciPy, How to do it..., How it works...
• SciPy 1.0
  • URL / What's new in the SciPy ecosystem?
• SciPy ecosystem
  • about / What is the SciPy ecosystem?, What's new in the SciPy ecosystem?
• Scott's Rule / How it works...
• seaborn
  • statistical plots, creating / Creating statistical plots easily with seaborn, How to do it..., There's more...
  • references / There's more...
• sequential locality / Why are NumPy arrays efficient?
• Shapefile
  • URL / Manipulating geospatial data with Cartopy
• shortest paths
  • URL / Problems in graph theory
• shortest paths, in NetworkX
  • references / There's more...
• sigmoid function / How it works...
• SIMD paradigm
  • about / Writing massively parallel code for NVIDIA graphics cards (GPUs) with CUDA
• Single Instruction, Multiple Data (SIMD) / Understanding the internals of NumPy to avoid unnecessary array copying, There's more...
• Singular Value Decomposition (SVD) / How it works...
• SnakeViz
  • reference / There's more...
• Sobel filter / How it works...
  • URL / There's more...
• sounds / Sounds
• sound synthesizer
  • creating, in Notebook / Creating a sound synthesizer in the Notebook, How to do it..., How it works...
• spam filtering / Supervised learning
• sparse decomposition
  • about / Compressed sensing
• sparse matrices
  • about / There's more...
  • reference / There's more...
• sparse matrix / How to do it...
• spatial locality / Why are NumPy arrays efficient?
• Sphinx
  • URL / How to do it...
• Split Bregman algorithm
  • URL / There's more...
• Split Bregman method / How it works...
• Spyder / Integrated Development Environments
• state diagram / How it works...
• statistical data analysis
  • about / What is statistical data analysis?
• statistical hypothesis testing
  • about / Getting started with statistical hypothesis testing — a simple z-test, How to do it..., How it works...
  • URL / There's more...
• statistical inference
  • about / Exploration, inference, decision, prediction
• Statistical Learning
  • URL / Machine learning references
• statistical plots
  • creating, with seaborn / Creating statistical plots easily with seaborn, How to do it..., There's more...
• statistics
  • references / Parametric and nonparametric inference methods
• statistics resources
  • URL / Parametric and nonparametric inference methods
• stats module / How it works...
  • URL / There's more...
• Stochastic cellular automata / Introduction
• Stochastic differential equations (SDEs)
  • simulating / Simulating a stochastic differential equation, How to do it..., How it works...
• Stochastic Differential Equations (SDEs) / Introduction
  • URL / There's more...
• stochastic dynamical systems / Introduction
  • URL / References
• Stochastic Partial Differential Equations (SPDEs) / Introduction
• Stochastic processes
  • URL / References
• stream processors / How it works...
• strided indexing scheme / How it works...
• strides / Why can't some arrays be reshaped without a copy?
• stride tricks
  • using, in NumPy / Using stride tricks with NumPy, How to do it..., How it works...
  • used, for implementing rolling average algorithm / Implementing an efficient rolling average algorithm with stride tricks, How to do it...
• structure tensor / How it works...
  • URL / There's more...
• structuring element / How it works...
• Sum of Products
  • URL / There's more...
• supervised learning / Learning from data, Supervised learning
• Support Vector Classifier (SVC) / How to do it...
• support vector machines (SVM)
  • using, for classification tasks / Using support vector machines for classification tasks, How to do it..., How it works...
  • URL / Using support vector machines for classification tasks
  • references / There's more...
• SVD decomposition
  • URL / There's more...
• symbolic computing
  • exploring, with SymPy / Diving into symbolic computing with SymPy, How to do it..., See also
• SymPy / Introduction
  • used, for symbolic computing exploration / Diving into symbolic computing with SymPy, How to do it..., See also
  • equations, solving / Solving equations and inequalities, How to do it...
  • inequalities, solving / Solving equations and inequalities, How to do it...
  • probabilities, computing / Computing exact probabilities and manipulating random variables, How to do it..., How it works...
  • random variables, manipulating / Computing exact probabilities and manipulating random variables, How to do it..., How it works...
  • number theory / A bit of number theory with SymPy, How to do it..., How it works..., There's more...
• synthesizer
  • URL / There's more...

T

• t-Distributed Stochastic Neighbor Embedding (t-SNE)
  • references / There's more...
• term frequency-inverse document frequency (tf-idf) / How it works...
  • URL / There's more...
• Test-driven development (TDD)
  • about / Workflows with unit testing
  • URL / Unit testing and continuous integration
• test functions for optimization
  • URL / How to do it...
• test set / Supervised learning
• test statistic
  • about / How to do it...
• text feature extraction
  • URL / There's more...
• thread / How it works...
• Tikhonov regularization
  • URL / Ridge regression
• timbre / How it works...
• time series
  • about / Introduction, How it works...
  • autocorrelation, computing / Computing the autocorrelation of a time series, How to do it...
  • references / There's more...
• topological sort documentation
  • URL / There's more...
• topological sorting
  • dependencies, resolving in directed acyclic graph / Resolving dependencies in a directed acyclic graph with a topological sort, How to do it..., How it works..., There's more...
  • URL / There's more...
• total variation / How it works...
• total variation denoising / How it works...
• trace module
  • reference / There's more...
• training set / Supervised learning
• traitlets package
  • URL / Mastering IPython's configuration system
• transition matrix / How it works...
• Travis CI
  • URL / Unit testing and continuous integration
• two-dimensional array / How to do it...

U

• underfitting / Overfitting, underfitting, and the bias-variance tradeoff
• Uniform Manifold Approximation and Projection (UMAP)
  • URL / There's more...
• uninformative priors
  • URL / Non-informative (objective) prior distributions
• United States Census Bureau
  • URL / How to do it...
• unit tests
  • writing, with py.test / Writing unit tests with pytest, How to do it..., How it works...
  • test coverage / Test coverage
  • workflows / Workflows with unit testing
• univariate method
  • about / Univariate and multivariate methods
• Unix shell
  • about / Learning the basics of the Unix shell, How to do it..., There's more...
  • references / There's more...
• unsupervised learning / Learning from data
  • about / Unsupervised learning
  • clustering / Unsupervised learning
  • density estimation / Unsupervised learning
  • dimension reduction / Unsupervised learning
  • manifold learning / Unsupervised learning
  • URL / There's more...
• unsupervised learning methods / Reducing the dimensionality of a dataset with a principal component analysis

V

• Vandermonde matrix
  • URL / Polynomial interpolation with linear regression
• variable / Learning from data
• variance / Overfitting, underfitting, and the bias-variance tradeoff
• vector / How it works...
• vectorized instructions / Why are NumPy arrays efficient?
• vectorizer
  • URL / There's more...
• Vega / There's more..., Creating plots with Altair and the Vega-Lite specification
• Vega-Lite
  • plots, creating / Creating plots with Altair and the Vega-Lite specification, How to do it..., How it works..., There's more...
  • references / There's more...
• vertices
  • about / Graphs
• views / What is the difference between in-place and implicit-copy operations?
• Viola-Jones object detection framework / How to do it...
  • URL / There's more...
• VirtualBox
  • URL / Getting ready
• vocabulary / How to do it...
• voice frequency
  • URL / There's more...
• Voronoi diagram
  • computing, of set of points / Computing the Voronoi diagram of a set of points, How to do it..., How it works...
  • URL / There's more...

W

• wavelet transform / Inverse Fourier transform
• white box model / How it works...
• white noise / How it works...
  • URL / There's more...
• Wiener process / Simulating a Brownian motion
  • URL / There's more...
• Windows compilers
  • URL / Compiler-related installation instructions
• Windows operating system
  • URL / Learning the basics of the Unix shell
• Wolfram code
  • URL / There's more...

X

• xarray library
  • URL / There's more...

Z

• Zachary's Karate Club graph / How to do it...
• ZeroMQ (ZMQ)
  • URL / Architecture of the Jupyter Notebook