Mastering Machine Learning Algorithms

Explore the best approach for solving complex machine learning problems.
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Mastering Machine Learning Algorithms

Giuseppe Bonaccorso

Explore the best approach for solving complex machine learning problems.
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Book Details

ISBN 139781788621113
Paperback605 pages

Book Description

Machine learning is a subset of AI which aims at making modern-day computers smarter, and intelligent. The real power of machine learning resides in its algorithms which make even the most difficult things possible for machines to handle. However, with the advancement in the technology and requirement of data, our machines will have to be smarter than they are today to meet the overwhelming needs, and knowing how different algorithms work to make ML effective is the need of the hour.

Mastering Machine Learning Algorithms is your tool, your guide to get to grips quickly with the most widely used algorithms. You start with learning various ML models along with an introduction to semi-supervised learning. A firm grip on Bayesian networks, MCMC algorithm, Hidden Markov Models with examples will help you model a sequence of probabilistic events and infer future states.

You will continue to explore different algorithms and will be mesmerised to see the possibilities that lie ahead. Advanced clustering techniques are discussed with examples to help you uncover the extract features using Scikit-Learn. Example based discussion using Keras will help you get into the world of Deep learning, the next generation of machine learning. Overall, this book should be in your armoury for studying, implementing, and solving end-to-end problems using the ML algorithms.

Table of Contents

What You Will Learn

  • Explore how a ML model can be trained, optimised and evaluated
  • Understand how to create and learn static and dynamic probabilistic models
  • Successfully cluster high-dimensional data and evaluate the model accuracy
  • Discover how artificial neural networks work and how to train, optimise and validate them
  • Discovering Auto-encoders and Hopfield networks
  • Apply Label spreading and propagation to large datasets
  • Explor the most powerful Reinforcement Learning techniques with real-world applications

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Table of Contents

Book Details

ISBN 139781788621113
Paperback605 pages
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