Mastering Machine Learning Algorithms

More Information
Learn
  • Explore how a ML model can be trained, optimized, and evaluated
  • Understand how to create and learn static and dynamic probabilistic models
  • Successfully cluster high-dimensional data and evaluate model accuracy
  • Discover how artificial neural networks work and how to train, optimize, and validate them
  • Work with Autoencoders and Generative Adversarial Networks
  • Apply label spreading and propagation to large datasets
  • Explore the most important Reinforcement Learning techniques
About

Machine learning is a subset of AI that aims to make modern-day computer systems smarter and more intelligent. The real power of machine learning resides in its algorithms, which make even the most difficult things capable of being handled by machines. However, with the advancement in the technology and requirements of data, machines will have to be smarter than they are today to meet the overwhelming data needs; mastering these algorithms and using them optimally is the need of the hour.

Mastering Machine Learning Algorithms is your complete guide to quickly getting to grips with popular machine learning algorithms. You will be introduced to the most widely used algorithms in supervised, unsupervised, and semi-supervised machine learning, and will learn how to use them in the best possible manner. Ranging from Bayesian models to the MCMC algorithm to Hidden Markov models, this book will teach you how to extract features from your dataset and perform dimensionality reduction by making use of Python-based libraries such as scikit-learn. You will also learn how to use Keras and TensorFlow to train effective neural networks.

If you are looking for a single resource to study, implement, and solve end-to-end machine learning problems and use-cases, this is the book you need.

Features
  • Discover high-performing machine learning algorithms and understand how they work in depth.
  • One-stop solution to mastering supervised, unsupervised, and semi-supervised machine learning algorithms and their implementation.
  • Master concepts related to algorithm tuning, parameter optimization, and more
Page Count 576
Course Length 17 hours 16 minutes
ISBN 9781788621113
Date Of Publication 24 May 2018

Authors

Giuseppe Bonaccorso

Giuseppe Bonaccorso is an experienced manager in the fields of AI, data science, and machine learning. He has been involved in solution design, management, and delivery in different business contexts. He got his M.Sc.Eng in electronics in 2005 from the University of Catania, Italy, and continued his studies at the University of Rome Tor Vergata, Italy, and the University of Essex, UK. His main interests include machine/deep learning, reinforcement learning, big data, bio-inspired adaptive systems, neuroscience, and natural language processing.