Mastering Machine Learning Algorithms (Second Edition)

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Mastering Machine Learning Algorithms (Second Edition)

- Expert techniques for implementing popular machine learning algorithms, fine-tuning your models, and understanding how they work
 Author: Giuseppe Bonaccorso  Publisher: Packt Publishing  ISBN: 1838820299  ISBN: 978-1838820299  ASIN: B0843PMXPV  Pages: 798  Language: English  Buy Now  Amazon  Amazon Kindle  Google Play
 Description:

Updated and revised second edition of the bestselling guide to exploring and mastering the most important algorithms for solving complex machine learning problems

Key Features

    • Updated to include new algorithms and techniques
    • Code updated to Python 3.8 & TensorFlow 2.x
    • New coverage of regression analysis, time series analysis, deep learning models, and cutting-edge applications

Book Description

Mastering Machine Learning Algorithms, Second Edition helps you harness the real power of machine learning algorithms to implement smarter ways of meeting today’s overwhelming data needs. This newly updated and revised guide will help you master algorithms used widely in semi-supervised learning, reinforcement learning, supervised learning, and unsupervised learning domains.

You will use all the modern libraries from the Python ecosystem – including NumPy and Keras – to extract features from varied complexities of data. Ranging from Bayesian models to the Markov chain Monte Carlo algorithm to Hidden Markov models, this machine learning book teaches you how to extract features from your dataset, perform complex dimensionality reduction, and train supervised and semi-supervised models by making use of Python-based libraries such as scikit-learn. You will also discover practical applications for complex techniques such as maximum likelihood estimation, Hebbian learning, and ensemble learning, as well as how to use TensorFlow 2.x to train effective deep neural networks.

By the end of this book, you will be ready to implement and solve end-to-end machine learning problems and use case scenarios.

What you will learn

    • Understand the characteristics of a machine learning algorithm
    • Implement algorithms from supervised, semi-supervised, unsupervised, and RL domains
    • Learn how regression works in time-series analysis and risk prediction
    • Create, model, and train complex probabilistic models
    • Cluster high-dimensional data and evaluate model accuracy
    • Discover how artificial neural networks work – train, optimize, and validate them
    • Work with autoencoders, Hebbian networks, and GANs

Who this book is for

This book is for data science professionals who want to explore complex ML algorithms to understand how various machine learning models can be built. Knowledge of Python programming is required.

You might also be interested in my Technical Posts, which contain addenda and related topics.

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Editorial Reviews

"This new second edition of Mastering Machine Learning Algorithms provides an essential overview of everything you need to know to be able to solve advanced machine learning problems, from A-to-Z: from Algorithms, Artificial Neural Networks, and AdaBoost to normaliZation, optimiZation, and regulariZation, and everything in between. Given the complexity of many of these algorithms, this accomplishment is no small task, and this is no small book. The book's comprehensive contents deliver a rich source of machine learning knowledge."

Dr Kirk Borne, Principal Data Scientist, Data Science Fellow, and Executive Advisor at Booz Allen Hamilton, and co-author of Ten Signs of Data Science Maturity

"Machine Learning is an essential part of the Artificial Intelligence toolkit. Good and detailed understanding of machine learning helps in creating value from data through Artificial Intelligence. Get this book! This book will build on top of your existing understanding of machine learning and it covers a good range of machine learning models from Markov Models to Deep Learning models used in the industry."

Koo Ping Shung, Co-founder & Practicum Director at Data Science Rex, and Co-founder of DataScience SG

Other Books By - Giuseppe Bonaccorso


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