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Statistics for Machine Learning

You're reading from Statistics for Machine Learning Techniques for exploring supervised, unsupervised, and reinforcement learning models with Python and R

Product type Paperback

Published in Jul 2017

Publisher Packt

ISBN-13 9781788295758

Length 442 pages

Edition 1st Edition

Languages

Python

Concepts

Machine Learning

Author (1):

Pratap Dangeti

View More author details

Table of Contents (10) Chapters

Preface

1. Journey from Statistics to Machine Learning FREE CHAPTER

2. Parallelism of Statistics and Machine Learning

3. Logistic Regression Versus Random Forest

4. Tree-Based Machine Learning Models

5. K-Nearest Neighbors and Naive Bayes

6. Support Vector Machines and Neural Networks

7. Recommendation Engines

8. Unsupervised Learning

9. Reinforcement Learning

Recommendation Engines

Recommendation engines (REs) are most famously used for explaining what machine learning is to any unknown person or a newbie who wants to understand the field of machine learning. A classic example could be how Amazon recommends books similar to the ones you have bought, which you may also like very much! Also, empirically, the recommender engine seems to be an example of large-scale machine learning that everyone understands, or perhaps already understood. But, nonetheless, recommendation engines are being used everywhere. For example, the people you may know feature in Facebook or LinkedIn, which recommends by showing the most probable people you might like to befriend or professionals in your network who you might be interested in connecting with. Of course, these features drive their businesses big time and it is at the heart of the company's driving...

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Authors (1)

Pratap Dangeti

Pratap Dangeti

Pratap Dangeti is currently working as a Senior Data Scientist at Bidgely Technologies Bangalore. He has a vast experience in analytics and data science. He received his master's degree from IIT Bombay in its industrial engineering and operations research program. Pratap is an artificial intelligence enthusiast. When not working, he likes to read about next-gen technologies and innovative methodologies.

See other products by Pratap Dangeti

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