Book Image

Statistics for Machine Learning

By : Pratap Dangeti
Book Image

Statistics for Machine Learning

By: Pratap Dangeti

Overview of this book

Complex statistics in machine learning worry a lot of developers. Knowing statistics helps you build strong machine learning models that are optimized for a given problem statement. This book will teach you all it takes to perform the complex statistical computations that are required for machine learning. You will gain information on the statistics behind supervised learning, unsupervised learning, reinforcement learning, and more. You will see real-world examples that discuss the statistical side of machine learning and familiarize yourself with it. You will come across programs for performing tasks such as modeling, parameter fitting, regression, classification, density collection, working with vectors, matrices, and more. By the end of the book, you will have mastered the statistics required for machine learning and will be able to apply your new skills to any sort of industry problem.
Table of Contents (16 chapters)
Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

Summary


In this chapter, you have learned about the most computationally intensive methods, SVMs and neural networks. Support vector machines perform really well on data in which the number of dimensions is very high, where other methods fail to work. By utilizing kernels, SVMs can reach very high test accuracies; we have covered how kernels actually work in detail in this chapter. Neural networks have become very popular in recent times for solving various problems; here, we covered all the deep learning fundamentals required for building a neural network model using both scikit-learn and Keras. In addition, results were compared between scikit-learn and Keras models to show apple-to-apple comparison. By utilizing deep learning, many new-generation artificial intelligence problems can be solved, whether it is text, voice, images, videos, and so on. In fact, deep learning itself has become a separate domain altogether.

In the next chapter, we will be looking at recommendation engines using...