Index

A

• activation functions
  • implementing / Getting ready, How to do it…, How it works…, There's more…
  • used, for implementing gates / Working with Gates and Activation Functions, How to do it…, How it works…, There's more…
  • sigmoid / Getting ready
  • rectified linear unit (ReLU) / Getting ready
• address matching example
  • using / Using an Address Matching Example, How to do it…, How it works…
• advanced CNN
  • implementing / Implementing an Advanced CNN, Getting ready, How to do it…, How it works…
• Amazon Web Services (AWS)
  • about / There's more…
• Amherst statistical dataset repository
  • URL / Getting ready
• Anaconda package
  • URL / Getting ready
• Arxiv.org
  • about / There's more…
• AWS machine images (AMIs)
  • about / There's more…

B

• back propagation
  • implementing / Implementing Back Propagation, Getting ready, How to do it…, There's more…
  • advantages / There's more…
  • usage / There's more…
  • disadvantages / There's more…
• bag of words
  • implementing / Working with bag of words, How to do it…, There's more…
• batch training
  • implementing / Working with Batch and Stochastic Training, How to do it…, How it works…
  • advantages / There's more…
  • disadvantages / There's more…
• bilingual sentence dataset
  • URL / There's more…
• birth weight data
  • about / How to do it…
• Boston Housing data
  • about / How to do it…

C

• CIFAR-10 dataset
  • URL / See also
• CIFAR-10 image data
  • about / How to do it…
  • URL / How to do it…
• CIFAR10 dataset
  • URL / Getting ready
• classifier
  • creating, on iris dataset / Combining Everything Together, Getting ready, How to do it…, There's more…
• clustering
  • with k-means / Clustering Using K-Means, How to do it…, There's more…
• command line
  • graphs, visualizing / There's more…
• computational graph
  • operations, creating / Operations in a Computational Graph, How to do it…
• Continuous bag of words (CBOW) method
  • about / Getting ready
  • implementing / Working with CBOW Embeddings, Getting ready, How to do it…, How it works…
• convolution
  • about / Introduction
• Convolutional Neural Networks (CNNs)
  • about / Introduction
  • resources / See also
• cross entropy
  • about / How to do it

D

• data sources
  • about / Working with Data Sources
  • using / Getting ready, How to do it…, How it works…
  • iris data / How to do it…
  • birth weight data / How to do it…
  • Boston Housing data / How to do it…
  • MNIST handwriting data / How to do it…
  • spam-ham text data / How to do it…
  • movie review data / How to do it…
  • CIFAR-10 image data / How to do it…
  • works of Shakespeare text data / How to do it…
  • English-German sentence translation data / How to do it…
• decoding
  • about / Introduction
• decomposition method
  • implementing / Implementing a Decomposition Method, How to do it…, How it works…
• Deepdream
  • implementing / Implementing DeepDream, How to do it…, There's more…
  • references / See also
• Deming regression
  • implementing / Implementing Deming regression, Getting ready, How to do it…, How it works…
• Doc2vec
  • used, for sentiment analysis / Using Doc2vec for Sentiment Analysis, Getting ready, How to do it…, How it works…

E

• elastic net regression
  • implementing / Implementing Elastic Net Regression, How to do it…
• encoding
  • about / Introduction
• English-German sentence translation data
  • about / How to do it…
• epoch
  • about / There's more…
• existing CNNs models
  • retraining / Retraining Existing CNNs models, Getting ready, How to do it…
• Exponential Linear Unit (ELU)
  • about / How to do it…

G

• gates
  • implementing, with activation functions / Working with Gates and Activation Functions, How to do it…, How it works…, There's more…
• genetic algorithm
  • implementing / Working with a Genetic Algorithm, Getting ready, How to do it…, How it works…, There's more…
• graphs
  • visualizing, in Tensorboard / Visualizing graphs in Tensorboard, Getting ready, How to do it…
  • visualizing, from command line / There's more…

H

• Hello World program
  • writing, for image recognition / Getting ready

I

• image recognition
  • with nearest neighbors / Getting ready, How to do it…, How it works…
• Inception
  • about / Getting ready
  • reference link / See also
• iris data
  • about / How to do it…
• iris dataset
  • classifier, creating / Combining Everything Together, Getting ready, How to do it…, There's more…
  • references / See also

K

• k-means
  • used, for clustering / Clustering Using K-Means, How to do it…, There's more…
• k-nearest neighbors (k-NN)
  • about / Introduction
• Kernels
  • implementing, in TensorFlow / Working with Kernels in TensorFlow, Getting ready, How to do it…, How it works…, There's more…

L

• lasso regression
  • implementing / Implementing Lasso and Ridge Regression, How to do it…, How it works…
• Levenshtein distance / Getting ready
• linear models
  • predictions, improving / Improving the Predictions of Linear Models, How to do it, How it works…
• linear regression
  • about / Introduction
  • in TensorFlow / Getting ready, How to do it…, How it works…
  • loss functions, implementing / Understanding Loss Functions in Linear Regression, How to do it…, How it works…
  • implementing / Reduction to Linear Regression, Getting ready, How to do it…, How it works…
• linear separator
  • defining / Introduction
• linear SVM
  • implementing / Working with a Linear SVM, How to do it…, How it works…
• logistic regression
  • implementing / Implementing Logistic Regression, How to do it…, How it works…
• Long Short Term Memory (LSTM)
  • about / Introduction, Getting ready
• loss functions
  • implementing / Implementing Loss Functions, How to do it…, How it works…, There's more…
  • usage / There's more…
  • benefits / There's more…
  • disadvantages / There's more…
  • in linear regression / Understanding Loss Functions in Linear Regression, How to do it…, How it works…
• LSTM model
  • implementing / Implementing an LSTM Model, Getting ready, How to do it…, How it works…

M

• ManyThings.org
  • URL / How to do it…
• math functions
  • abs() / How to do it…
  • ceil() / How to do it…
  • cos() / How to do it…
  • exp() / How to do it…
  • floor() / How to do it…
  • inv() / How to do it…
  • log() / How to do it…
  • maximum() / How to do it…
  • minimum() / How to do it…
  • neg() / How to do it…
  • pow() / How to do it…
  • round() / How to do it…
  • rsqrt() / How to do it…
  • sign() / How to do it…
  • sin() / How to do it…
  • sqrt() / How to do it…
  • square() / How to do it…
• matrices
  • about / Working with Matrices
  • creating / How to do it…
• matrix inverse method
  • using / Using the Matrix Inverse Method, How to do it…, How it works…
• mean squared error (MSE) / How to do it…
• mixed distance functions
  • computing with / Computing with Mixed Distance Functions, Getting ready, How to do it…, How it works…, There's more…
• MNIST (Mixed National Institute of Standards and Technology) / How to do it…
• MNIST handwriting data
  • about / How to do it…
  • URL / How to do it…
• model metric
  • R-squared (coefficient of determination) / There's more…
  • RMSE (root mean squared error) / There's more…
  • Confusion matrix / There's more…
  • Recall / There's more…
  • Precision / There's more…
  • F-score / There's more…
• models
  • evaluating / Evaluating Models, How it works…
• movie review data
  • about / How to do it…
  • URL / How to do it…, Getting ready
• multi-class SVM
  • implementing / Implementing a Multi-Class SVM, Getting ready, How to do it…, How it works…
• multilayer neural network
  • implementing / Using a Multilayer Neural Network, How to do it…
• multiple executors
  • using / Using Multiple Executors, How to do it…, How it works…
• multiple layers
  • connecting / Working with Multiple Layers, How to do it…, How it works…
• multiple LSTM Layers
  • stacking / Stacking multiple LSTM Layers, Getting ready, How to do it…, How it works…

N

• nearest neighbors
  • implementing / Working with Nearest Neighbors, Getting ready, How to do it…, How it works…
  • used, for image recognition / Getting ready, How to do it…, How it works…
  • reference link / There's more…
• nested operations
  • layering / Layering Nested Operations, How to do it…, There's more…
• neural network (nn) library
  • about / How to do it…
• neural networks
  • about / Introduction
  • resources / Introduction
  • different layers, implementing / Implementing Different Layers, Getting ready, How to do it…, How it works…
• non-linear SVM
  • implementing / Implementing a Non-Linear SVM, How to do it…
• Nvidia Cuda Toolkit
  • URL / Getting ready

O

• one layer neural network
  • implementing / Implementing a One-Layer Neural Network, How to do it…, There's more…
• operational gates
  • implementing / Implementing Operational Gates, How to do it…, How it works…
• operations
  • declaring / Declaring Operations, How to do it…, There's more…
  • creating, in computational graph / Operations in a Computational Graph, How to do it…
  • nested operations, layering / Layering Nested Operations, How it works…, There's more…
• ordinary differential equations (ODEs)
  • about / Getting ready

P

• placeholders
  • about / Using Placeholders and Variables
  • using / Using Placeholders and Variables, How it works…, There's more…
• predictions
  • estimating, with Word2vec / Making Predictions with Word2vec, How to do it…, How it works…, There's more…
• Python 3.4+
  • URL / Getting ready
• Python Image Library (PIL) / How to do it…

R

• rectified linear unit (ReLU)
  • about / Getting ready
  • advantages / How it works…
  • disadvantages / How it works…
• recurrent neural network (RNN)
  • about / Introduction
  • implementing, for spam prediction / Implementing RNN for Spam Prediction, Getting ready, How to do it…, There's more…
• ridge regression
  • implementing / Implementing Lasso and Ridge Regression, How to do it…, How it works…

S

• sentiment analysis
  • with Doc2vec / Using Doc2vec for Sentiment Analysis, How to do it…, How it works…
• sequence-to-sequence models
  • creating / Creating Sequence-to-Sequence Models, How to do it…, How it works…
  • creating / How to do it…
• Siamese similarity measure
  • training / Training a Siamese Similarity Measure, How to do it…, There's more…
• sigmoid
  • about / Getting ready
  • advantages / How it works…
  • disadvantages / How it works…
• simpler CNN
  • implementing / Implementing a Simpler CNN, How to do it…, How it works…
• skip-gram embedding
  • implementing / Working with Skip-gram Embeddings, Getting ready, How to do it…, How it works…
• spam-ham phone text database
  • URL / Getting ready
• spam-ham text data
  • about / How to do it…
• spam prediction
  • recurrent neural network (RNN), implementing / Implementing RNN for Spam Prediction, Getting ready, How to do it…, There's more…
• specialty mathematical functions
  • about / How to do it…
  • digamma() / How to do it…
  • erf() / How to do it…
  • erfc() / How to do it…
  • igamma() / How to do it…
  • igammac() / How to do it…
  • lbeta() / How to do it…
  • lgamma() / How to do it…
  • squared_difference() / How to do it…
• stochastic training
  • implementing / Working with Batch and Stochastic Training, How to do it…, How it works…
  • advantages / There's more…
  • disadvantages / There's more…
• Stylenet/Neural-Style
  • applying / Applying Stylenet/Neural-Style, Getting ready, How to do it…, How it works…
• system of ODEs
  • solving / Solving a System of ODEs, How to do it…

T

• Tatoeba Project
  • URL / Getting ready
• Tatoeba project
  • URL / How to do it…
• Tensorboard
  • graphs, visualizing / Visualizing graphs in Tensorboard, Getting ready, How to do it…
  • graphs, visualizing from command line / There's more…
• TensorFlow
  • computation / How TensorFlow Works, How it works…
  • tutorials, URL / See also
  • resources / Additional Resources
  • resources, URL / How to do it…
  • linear regression, implementing / Getting ready, How to do it…, How it works…
  • Kernels, implementing / Working with Kernels in TensorFlow, Getting ready, How to do it…, How it works…, There's more…
  • GPU version, URL / Getting ready
  • parallelizing / Parallelizing TensorFlow, How to do it…
  • best practices / Taking TensorFlow to Production, How to do it…, How it works…
  • productionalizing, with example / Productionalizing TensorFlow – An Example, How to do it…
• TensorFlow 0.12
  • URL / Getting ready
• TensorFlow Distributed / Getting ready
• TensorFlow Python API
  • URL / See also
• tensors
  • about / Declaring Tensors
  • declaring / Declaring Tensors, How to do it…, How it works…, There's more…
• text based distances
  • measuring / Getting ready, How to do it…, How it works…
  • Hamming distance / There's more…
  • Cosine distance / There's more…
  • Jaccard distance / There's more…
• Text Frequency - Inverse Document Frequency (TF-IDF)
  • implementing / Implementing TF-IDF, Getting ready, How to do it…, How it works…
  • about / Getting ready
• Tic Tac Toe
  • moves, learning / Learning to Play Tic Tac Toe, Getting ready, How to do it…, How it works…
  • reference link / Getting ready

U

• unit tests
  • implementing / Implementing unit tests, Getting ready
  • reference link / How it works…

V

• variables
  • about / Using Placeholders and Variables
  • using / Using Placeholders and Variables, How it works…, There's more…

W

• Word2vec
  • about / Getting ready
  • used, for estimating predictions / Making Predictions with Word2vec, How to do it…, How it works…, There's more…
• workflow, TensorFlow
  • dataset, importing / How to do it…
  • dataset, generating / How to do it…
  • data, normalizing / How to do it…
  • data, transforming / How to do it…
  • dataset, partitioning / How to do it…
  • algorithm parameters, setting / How to do it…
  • variables, initializing / How to do it…
  • placeholders, initializing / How to do it…
  • model structure, defining / How to do it…
  • loss functions, declaring / How to do it…
  • model, initializing / How to do it…
  • model, training / How to do it…
  • model, evaluating / How to do it…
  • hyperparameters, tuning / How to do it…
  • outcomes, deploying / How to do it…
  • outcomes, predicting / How to do it…
• works of Shakespeare text data
  • about / How to do it…