Practical machine learning cookbook

✍ Scribed by Atul Tripathi

Publisher: Packt Publishing
Year: 2017
Tongue: English
Leaves: 558
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

Machine learning has become the new black. The challenge in today’s world is the explosion of data from existing legacy data and incoming new structured and unstructured data. The complexity of discovering, understanding, performing analysis, and predicting outcomes on the data using machine learning algorithms is a challenge. This cookbook will help solve everyday challenges you face as a data scientist. The application of various data science techniques and on multiple data sets based on real-world challenges you face will help you appreciate a variety of techniques used in various situations.

The first half of the book provides recipes on fairly complex machine-learning systems, where you’ll learn to explore new areas of applications of machine learning and improve its efficiency. That includes recipes on classifications, neural networks, unsupervised and supervised learning, deep learning, reinforcement learning, and more.

The second half of the book focuses on three different machine learning case studies, all based on real-world data, and offers solutions and solves specific machine-learning issues in each one.

✦ Table of Contents

Introduction to Machine Learning
Classification
Clustering
Model Selection and Regularization
Nonlinearity
Supervised Learning
Unsupervised Learning
Reinforcement Learning
Structured Prediction
Neural Networks
Deep Learning
Case Study - Exploring World Bank Data
Case Study - Pricing Reinsurance Contracts
Case Study - Forecast of Electricity Consumption

✦ Subjects

R, Machine Learning

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