Home | Amazing | Today | Tags | Publishers | Years | Account | Search 
Mastering Machine Learning Algorithms: Expert techniques to implement popular machine learning algorithms and fine-tune your models

Buy

Explore and master the most important algorithms for solving complex machine learning problems.

Key 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

Book Description

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.

What you will 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

Who This Book Is For

This book is an ideal and relevant source of content for data science professionals who want to delve into complex machine learning algorithms, calibrate models, and improve the predictions of the trained model. A basic knowledge of machine learning is preferred to get the best out of this guide.

Table of Contents

  1. Machine Learning Model Fundamentals
  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
  7. Advanced Clustering and Feature Extraction
  8. Ensemble Learning
  9. Neural Networks for Machine Learning
  10. Advanced Neural Models
  11. Auto-Encoders
  12. Generative Adversarial Networks
  13. Deep Belief Networks
  14. Introduction to Reinforcement Learning
  15. Policy estimation algorithms
(HTML tags aren't allowed.)

Advances in Biometrics: Sensors, Algorithms and Systems
Advances in Biometrics: Sensors, Algorithms and Systems

Biometrics technology continues to stride forward with its wider acceptance and its real need in various new security facets of modern society. From simply logging on to a laptop to crossing the border of a country, biometrics is being called upon to meet the growing challenges of identity management.

With contributions from academia and...

Core Java Volume I--Fundamentals (9th Edition) (Core Series)
Core Java Volume I--Fundamentals (9th Edition) (Core Series)

Fully updated to reflect Java SE 7 language changes, Core Java™, Volume I—Fundamentals, Ninth Edition, is the definitive guide to the Java platform.

 

Designed for serious programmers, this reliable, unbiased,...

Engineering Mega-Systems: The Challenge of Systems Engineering in the Information Age
Engineering Mega-Systems: The Challenge of Systems Engineering in the Information Age

With their ability to cross traditional boundaries and achieve a level of functionality greater than their component elements, mega-systems have helped corporations and government organizations around the world resolve complex challenges that they otherwise couldn’t address with stand-alone systems. Engineering Mega-Systems: The...


David Busch's Sony Alpha DSLR-A580/A560 Guide to Digital Photography (David Busch's Digital Photography Guides)
David Busch's Sony Alpha DSLR-A580/A560 Guide to Digital Photography (David Busch's Digital Photography Guides)

The new Sony Alpha DSLR-A580 and A560 are innovative new, mid-level dSLR models that will replace the A550 and A500 models. They are the first from Sony to include full HDTV video as well as sophisticated features such as 7 frames-per-second continuous shooting and Sweep Panorama, 16.7 (A580) and 14.6 (A560) megapixel resolutions. David...

Graphics Gems Iv/Book and Mac Version Disk (The Graphics Gems Series) (No.4)
Graphics Gems Iv/Book and Mac Version Disk (The Graphics Gems Series) (No.4)

We make images to communicate. The ultimate measure of the quality of our images is how well they communicate information and ideas from the creator’s mind to the perceiver’s mind. The efficiency of this communication, and the quality of our image, depends on both what we want to say and to whom we intend to say it. I believe that...

Algorithms in Combinatorial Design Theory (Mathematics Studies)
Algorithms in Combinatorial Design Theory (Mathematics Studies)
Recent years have seen an explosive growth in research in combinatorics and graph theory. One primary factor in this rapid development has been the advent of computers, and the parallel study of practical and efficient algorithms. This volume represents an attempt to...
©2021 LearnIT (support@pdfchm.net) - Privacy Policy