Packt+ | Advance your knowledge in tech

0

All Products

Best Sellers

New Releases

Books

Videos

Audiobooks

Free Learning

Mastering Machine Learning Algorithms

You're reading from Mastering Machine Learning Algorithms Expert techniques to implement popular machine learning algorithms and fine-tune your models

Product type Paperback

Published in May 2018

Publisher Packt

ISBN-13 9781788621113

Length 576 pages

Edition 1st Edition

Concepts

Machine Learning

Table of Contents (22) Chapters

Title Page

Dedication

Packt Upsell

Contributors

Preface

1. Machine Learning Model Fundamentals FREE CHAPTER

2. Introduction to Semi-Supervised Learning

3. Graph-Based Semi-Supervised Learning

4. Bayesian Networks and Hidden Markov Models

5. EM Algorithm and Applications

6. Hebbian Learning and Self-Organizing Maps

7. Clustering Algorithms

8. Ensemble Learning

9. Neural Networks for Machine Learning

10. Advanced Neural Models

11. Autoencoders

12. Generative Adversarial Networks

13. Deep Belief Networks

14. Introduction to Reinforcement Learning

15. Advanced Policy Estimation Algorithms

1. Other Books You May Enjoy

Leave a review - let other readers know what you think

Index

Self-organizing maps

Self-organizing maps (SOMs) have been proposed by Willshaw and Von Der Malsburg (Willshaw D. J., Von Der Malsburg C., How patterned neural connections can be set up by self-organization, Proceedings of the Royal Society of London, B/194, N. 1117) to model different neurobiological phenomena observed in animals. In particular, they discovered that some areas of the brain develop structures with different areas, each of them with a high sensitivity for a specific input pattern. The process behind such a behavior is quite different from what we have discussed up until now, because it's based on competition among neural units based on a principle called winner-takes-all. During the training period, all the units are excited with the same signal, but only one will produce the highest response. This unit is automatically candidate to become the receptive basin for that specific pattern. The particular model we are going to present has been introduced by Kohonen (in the paper...

The rest of the chapter is locked

Register for a free Packt account to unlock a world of extra content!

A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.

Unlock this book and the full library FREE for 7 days

Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of

Start free trial

Renews at $15.99/month. Cancel anytime

Other recommended products

Related to this chapter

Mastering Machine Learning Algorithms

Mastering Machine Learning Algorithms

A new second edition of the bestselling guide to exploring and mastering the most important algorithms for solving complex machine learning problems, updated to include Python 3.8 and TensorFlow 2.x as well as the latest in new algorithms and techniques.

Jan 2020 26h 36m

Hands-On Unsupervised Learning with Python

Hands-On Unsupervised Learning with Python

Unsupervised learning is a key required block in both machine learning and deep learning domains. You will explore how to make your models learn, grow, change, and develop by themselves whenever they are exposed to a new set of data. With this book, you will learn the art of unsupervised learning for different real-world challenges.

Feb 2019 12h 52m

Machine Learning Algorithms

Machine Learning Algorithms

Machine learning explores the study and construction of algorithms that can learn from and make predictions on data. This book will act as an entry point for anyone who wants to make a career in Machine Learning. It covers algorithms like Linear regression, Logistic Regression, SVM, Naïve Bayes, K-Means, Random Forest, and Feature engineering.

Aug 2018 17h 24m

Hands-On Markov Models with Python

Hands-On Markov Models with Python

This book will help you become familiar with HMMs and different inference algorithms by working on real-world problems. You will start with an introduction to the basic concepts of Markov chains, Markov processes and then delve deeper into understanding hidden Markov models and its types using practical examples.

Sep 2018 5h 56m

Machine Learning Algorithms

Machine Learning Algorithms

Machine learning explores the study and construction of algorithms that can learn from, and make predictions on, data. This book will act as an entry point for anyone who wants to make a career in the field of Machine Learning. A few famous algorithms that are covered in this book are Linear regression, Logistic Regression, SVM, Naïve Bayes, K-Means, Random Forest, TensorFlow, and Feature engineering.

Jul 2017 12h 0m

Hands-On Deep Learning Algorithms with Python

Hands-On Deep Learning Algorithms with Python

This book introduces basic-to-advanced deep learning algorithms used in a production environment by AI researchers and principal data scientists; it explains algorithms intuitively, including the underlying math, and shows how to implement them using popular Python-based deep learning libraries such as TensorFlow.

Jul 2019 17h 4m

Mastering Machine Learning with scikit-learn

Mastering Machine Learning with scikit-learn

This book examines machine learning models including k-nearest neighbors, logistic regression, naive Bayes, random forests, and support vector machines. You will work through document classification, image recognition, and other example problems.

Jul 2017 8h 28m

Hands-On Ensemble Learning with Python

Hands-On Ensemble Learning with Python

Ensemble learning can provide the necessary methods to improve the accuracy and performance of existing models. In this book, you'll understand how to combine different machine learning algorithms to produce more accurate results from your models.

Jul 2019 9h 56m

Mastering Java Machine Learning

Mastering Java Machine Learning

Master key Java machine learning libraries and their applications with the help of real-world case studies. Explore advanced machine learning techniques such as anomaly detection, stream learning, active learning, semi-supervised learning, probabilistic graph modeling, text mining, deep learning, and big data batch and stream machine learning.

Jul 2017 18h 32m

Scala for Machine Learning

Scala for Machine Learning

Scala is becoming the language of choice for software engineers and data scientists who analyze large data sets. This trend has been reinforced by the wide acceptance of Scala based frameworks such as Apache Spark and Kafka. As a functional language, Scala is particularly suited for extracting knowledge through supervised, unsupervised or reinforcement learning techniques. Being object-oriented, Scala ensured the construction of robust and maintainable software solutions. This book introduces the most common used machine learning models as implemented in Scala

Sep 2017 24h 40m

Deep Learning with Hadoop

Deep Learning with Hadoop

Feb 2017 6h 52m

Python Machine Learning

Python Machine Learning

This second edition of Python Machine Learning by Sebastian Raschka is for developers and data scientists looking for a practical approach to machine learning and deep learning. In this updated edition, you'll explore the machine learning process using Python and the latest open source technologies, including scikit-learn and TensorFlow 1.x.

Sep 2017 20h 44m

Personalised recommendations for you

Based on your interests and search pattern

Mathematics of Machine Learning

Mathematics of Machine Learning

Deepen your theoretical knowledge and enhance your ability to solve complex machine learning problems with structured guidance. Gain the confidence to engage with advanced ML literature and tailor algorithms to meet your project requirements.

May 2025 24h 20m

Generative AI with Python and PyTorch

Generative AI with Python and PyTorch

Learn how to create images and text using VAEs, GANs, LSTMs, and transformers. Implement applications in natural language processing and computer vision through practical tutorials.

Mar 2025 15h 0m

Practical Generative AI with ChatGPT

Practical Generative AI with ChatGPT

This book helps you unlock ChatGPT's potential to make your working life better. From prompt engineering to creating custom GPTs, you'll enhance your productivity, creativity, and efficiency with practical insights and advanced techniques.

Apr 2025 12h 52m

Generative AI with LangChain

Generative AI with LangChain

Gain a solid foundation in LangChain, agentic AI, and LangGraph, and learn to build production-ready systems with multi-agent architectures, advanced RAG pipelines, Tree of Thought reasoning, agent handoffs, and fine-grained error handling.

May 2025 15h 52m

Architecting Power BI Solutions in Microsoft Fabric

Architecting Power BI Solutions in Microsoft Fabric

Power BI provides several options to solve common data problems, and designing the correct solution for each scenario can be a daunting task. This book makes it easier by guiding you through designing optimal solutions using Power BI.

Apr 2025 14h 16m

Microsoft Identity and Access Administrator SC-300 Exam Guide

Microsoft Identity and Access Administrator SC-300 Exam Guide

This comprehensive guide covers key topics such as Microsoft Entra ID implementation, authentication and access management, external user management, and hybrid identity solutions, providing practical insights and techniques for SC-300 exam success.

Mar 2025 19h 48m

LLM Design Patterns

LLM Design Patterns

This book helps you gain practical skills to develop and deploy LLMs. You'll learn data prep, training, pruning, quantization, and evaluation, as well as explore RAG, advanced prompting, and optimization to build robust, scalable language models.

May 2025 17h 48m

Tableau Cookbook for Experienced Professionals

Tableau Cookbook for Experienced Professionals

Advance your Tableau knowledge beyond the basics, streamline dashboard performance, tackle advanced geospatial challenges, and unlock API potential while fortifying your corporate data infrastructure with proven best practices.

Apr 2025 12h 24m

Time Series Analysis with Spark

Time Series Analysis with Spark

This book offers a complete guide to time series analysis with Apache Spark and Databricks, covering essential concepts and advanced techniques including Generative AI to equip readers with skills for real-world challenges across industries.

Mar 2025 9h 56m

Hands-On Artificial Intelligence for IoT

Hands-On Artificial Intelligence for IoT

Transform IoT systems with the power of artificial intelligence using this hands-on guide. Dive into practical techniques and expert insights to innovate and optimize your IoT devices, making them smarter and more efficient.

May 2025 15h 44m