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Book Overview & Buying
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Table Of Contents
Machine Learning Quick Reference
By :
Machine Learning Quick Reference
By:
Overview of this book
Machine learning makes it possible to learn about the unknowns and gain hidden insights into your datasets by mastering many tools and techniques. This book guides you to do just that in a very compact manner.
After giving a quick overview of what machine learning is all about, Machine Learning Quick Reference jumps right into its core algorithms and demonstrates how they can be applied to real-world scenarios. From model evaluation to optimizing their performance, this book will introduce you to the best practices in machine learning. Furthermore, you will also look at the more advanced aspects such as training neural networks and work with different kinds of data, such as text, time-series, and sequential data. Advanced methods and techniques such as causal inference, deep Gaussian processes, and more are also covered.
By the end of this book, you will be able to train fast, accurate machine learning models at your fingertips, which you can easily use as a point of reference.
Table of Contents (13 chapters)
Preface
Free Chapter
Quantifying Learning Algorithms
Evaluating Kernel Learning
Performance in Ensemble Learning
Training Neural Networks
Time Series Analysis
Natural Language Processing
Temporal and Sequential Pattern Discovery
Probabilistic Graphical Models
Selected Topics in Deep Learning
Causal Inference
Advanced Methods
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