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MACHINE LEARNING WITH SCIKIT-LEARN QUICK START GUIDE : classification, regression, and ... clustering techniques in python by Kevin Jolly is a nonfiction available to read on EtoBox.
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Deploy supervised and unsupervised machine learning algorithms using scikit-learn to perform classification, regression, and clustering. Key Features Build your first machine learning model using scikit-learn Train supervised and unsupervised models using popular techniques such as classification, regression and clustering Understand how scikit-learn can be applied to different types of machine learning problems Book Description Scikit-learn is a robust machine learning library for the Python programming language. It provides a set of supervised and unsupervised learning algorithms. This book is the easiest way to learn how to deploy, optimize, and evaluate all of the important machine learning algorithms that scikit-learn provides. This book teaches you how to use scikit-learn for machine learning. You will start by setting up and configuring your machine learning environment with scikit-learn. To put scikit-learn to use, you will learn how to implement various supervised and unsupervised machine learning models. You will learn classification, regression, and clustering techniques to work with different types of datasets and train your models. Finally, you will learn about an effe
Who reads MACHINE LEARNING WITH SCIKIT-LEARN QUICK START GUIDE : classification, regression, and ... clustering techniques in python?
It is typically read by self-directed learners exploring a subject in depth.
Common subject areas: history, science, philosophy, social sciences.
- Author
- Kevin Jolly
- Publisher
- Packt Publishing, Limited
- Published
- 2018
- Language
- EN
- ISBN
- 9781789347371
- Category
- nonfiction
- Subjects
- Computer Science, Science, Artificial Intelligence (Ai)
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