Machine Learning Quick Reference

Your hands-on reference guide to develop, train and optimize your machine learning models
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Machine Learning Quick Reference

Rahul Kumar

Your hands-on reference guide to develop, train and optimize your machine learning models
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Book Details

ISBN 139781788830577
Paperback263 pages

Book Description

Learning about the unknowns and getting hidden insights from your datasets is possible via mastering many tools and techniques from machine learning. Machine Learning Quick Reference gives you access to this core practice in a very compact manner.

This book will prove to be a direct reference point for you while you develop your own machine learning models. It includes hands-on, easy to access techniques on a variety of topics such as model selection, performance tuning, training neural networks, time series analysis and a lot more. Get an in-depth understanding of the commonly used machine learning algorithms, as well as the performance measures and best practices to ensure optimum performance of your models. The book also includes the necessary theory and mathematical explanations wherever required to understand and apply the concepts in the best possible manner. Further, deep learning techniques like deep neural networks, Adversarial Networks: GAN, Bayesian, Deep Gaussian processes will take over your mind. Finally, you will have hands-on experience in dealing with the advanced methods like classification, clustering, imputation, and regression.

By the end, you will have mastered all the tips, tricks and hacks related to machine learning to ease your day to day tasks.

Table of Contents

What You Will Learn

  • Get a quick rundown of basics such as model selection, statistical modeling, and cross-validation
  • Choose the best machine learning algorithm that suits a particular problem
  • Explore kernel learning, neural networks, and time-series analysis
  • Train deep learning models and optimize them for maximum performance
  • Dive into bayesian techniques and sentiment analysis in your NLP solution
  • Implement probabilistic graphical models and causal inference
  • Measure and optimize the performance of your machine learning models

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Table of Contents

Book Details

ISBN 139781788830577
Paperback263 pages
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