October 2018
Intermediate to advanced
172 pages
4h 6m
English
Overview
"Machine Learning with scikit-learn Quick Start Guide" walks you through the essentials of implementing machine learning techniques using the scikit-learn library in Python. You will learn how to perform classification, regression, and clustering, enabling you to build practical machine learning models.
What this Book will help me do
- Understand the fundamentals of the scikit-learn library and its setup
- Learn to implement classification models for accurate categorization of data
- Explore regression techniques to predict continuous outcomes from data
- Dive into clustering methods to group unlabelled data effectively
- Build end-to-end machine learning projects with scalable pipelines
Author(s)
None Jolly is a skilled educator and expert in data science and machine learning, with a passion for imparting knowledge through practical examples and accessible language. With a broad technical background and extensive experience in Python programming and machine learning, the author presents a clear pathway for learners to progress in this dynamic field.
Who is it for?
This book is ideal for aspiring machine learning practitioners who are eager to learn and apply scikit-learn in Python. Readers should have an intermediate understanding of Python and a basic grasp of mathematical concepts such as linear algebra and probability. It's perfect for developers and data enthusiasts who wish to delve into machine learning with practical, hands-on projects.
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