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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

Activation functions

Activation functions are the mechanisms by which an artificial neuron processes information and passes it throughout the network. The activation function takes a single number and performs a certain fixed mathematical functional mapping on it. There are many different types of activation functions. The most popular ones are the following:

Sigmoid
Tanh
Relu
Linear

Sigmoid function: Sigmoid has the mathematical form σ(x) = 1 / (1+e−x). It takes a real-valued number and squashes it into a range between 0 and 1. Sigmoid is a popular choice, which makes calculating derivatives easy and is easy to interpret.

Tanh function: Tanh squashes the real-valued number into the range [-1, 1]. The output is zero-centered. In practice, tanh non-linearity is always preferred to sigmoid non-linearity. Also, it can be proved that tanh is scaled sigmoid neuron tanh(x) = 2σ (2x) − 1.

Rectified Linear Unit (ReLU) function: ReLU has become very popular in the last few years. It computes the function...

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Authors (1)

Pratap Dangeti

Pratap Dangeti

Pratap Dangeti develops machine learning and deep learning solutions for structured, image, and text data at TCS, analytics and insights, innovation lab in Bangalore. He has acquired a lot of experience in both analytics and data science. He received his master's degree from IIT Bombay in its industrial engineering and operations research program. He is an artificial intelligence enthusiast. When not working, he likes to read about next-gen technologies and innovative methodologies.

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