Book Image

Machine Learning Quick Reference

By : Rahul Kumar
Book Image

Machine Learning Quick Reference

By: Rahul Kumar

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 (18 chapters)
Title Page
Copyright and Credits
About Packt
Contributors
Preface
Index

What is ensemble learning?


Sometimes, one machine learning model is not good enough for a certain scenario or use case as it might not give you the desired accuracy, recall, and precision. Hence, multiple learning models—or an ensemble of models captures the pattern of the data and gives better output.

As an example, let's say we are trying to decide on a place where we would like to go in the summer. Typically, if we are planning for a trip, the suggestions for the place pours in from all corners. That is, these suggestions might come from our family, websites, friends, and travel agencies, and then we have to decide on the basis of a good experience that we had in the past:

  • Family: Let's say that whenever we have consulted a family member and listened to them, there has been a 60% chance that they were proven right and we ended up having a good experience on the trip.
  • Friends: Similarly, if we listen to our friends, they suggest places where we might have a good experience. In these instances...