Book Image

Practical Machine Learning Cookbook

By : Atul Tripathi
Book Image

Practical Machine Learning Cookbook

By: Atul Tripathi

Overview of this book

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 (21 chapters)
Practical Machine Learning Cookbook
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
14
Case Study - Forecast of Electricity Consumption

Binary clustering - math test


In the education system tests and examinations are major features. The advantage of examination system is that it can be one of the ways to differentiate between good and poor performers. The examination system puts the onus on students to upgrade for next standard for which they should appear and pass exams. It creates responsibility on students to study on regular basis. The exam systems prepare the students to meet the challenges of future. It helps them to analyze reason and communicate their ideas effectively in a fixed time period. On the other hand few draw backs are noticed such as slow learners cannot perform well in test and this creates inferior complexity among students.

Getting ready

In order to perform binary clustering, we shall be using a dataset collected on math tests.

Step 1 - collecting and describing data

The dataset titled math test shall be used. This is available in the TXT format titled math test.txt. The dataset is in standard format. There...