Fun with Machine Learning

Key Features

● Get familiar with the common machine learning problems and understand how to solve them.

● Understand the importance of different types of data and how to work with them effectively.

● Learn how to use machine learning and AutoML tools to solve real-world problems.

Description

“Fun with Machine Learning” is an essential guide for anyone looking to learn about machine learning and how it can be used to make informed business decisions.

The book covers the basics of machine learning, providing an overview of key concepts and terminology. To fully understand machine learning, it is important to have a basic understanding of statistics and mathematics. The book provides a simple introduction to these topics, making it easy for you to understand the core concepts. One of the key features of the book is its focus on AutoML tools. It introduces you to different AutoML tools and explains how to use them to simplify the data science processes. The book also shows how machine learning can be used to solve real-world business problems, such as predicting customer churn, detecting fraud, and optimizing marketing campaigns.

By the end of the book, you will be able to transform raw data into actionable insights with machine learning.

What you will learn

● Get a clear understanding of what machine learning is and how it works.

● Learn how to perform regression analysis using Orange.

● Understand how to implement classification In machine learning.

● Get to know more about the clustering and association algorithms.

● Analyze, visualize, manipulate, and forecast time series data with Orange.

Who this book is for

This book is for Machine Learning engineers, Machine Learning enthusiasts, Data Scientists, beginners, and students who are looking to implement machine learning techniques to solve real-life business problems. It is also a great resource for business leaders who are responsible for making data-driven decisions.

Table of Contents

1. Significance of Machine Learning in Today’s Business

2. Know Your Data

3. Up and Running With Analytical Tools

4. Machine Learning in a Nutshell

5. Regression Analysis

6. Classification

7. Clustering and Association

8. Time Series Forecasting

9. Image Analysis

10. Tips and Tricks