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Fun with Machine Learning: Simplify the Data Science process by automating repetitive and complex tasks using AutoMLНазвание: Fun with Machine Learning: Simplify the Data Science process by automating repetitive and complex tasks using AutoML
Автор: Arockia Liborious, Dr. Rik Das
Издательство: BPB Publications
Год: 2023
Страниц: 271
Язык: английский
Формат: pdf, epub (true)
Размер: 10.8 MB

Learn how to use AutoML to leverage Machine Learning for solving business problems.

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.

Jupyter Notebooks are a fork of the IPython project, which had its own IPython Notebook project. Jupyter is named for the three primary programming languages that it appears to support: Julia, Python, and R. Jupyter comes with the IPython kernel, which allows you to develop Python programs, although there are presently over 100 alternative kernels available. Auto ML libraries allow non-experts to use ML models and techniques without getting into the depth of Machine Learning algorithms.

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.

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