Python Machine Learning Mastery: 65 Scikit-Learn Projects for Building Classification, Regression, and Clustering Models with Datasets

Author:   Leonard Brooks
Publisher:   Independently Published
ISBN:  

9798275605556


Pages:   132
Publication Date:   22 November 2025
Format:   Paperback
Availability:   Available To Order   Availability explained
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Python Machine Learning Mastery: 65 Scikit-Learn Projects for Building Classification, Regression, and Clustering Models with Datasets


Overview

Unlock the power of machine learning with Python and Scikit-Learn through hands-on projects that transform theory into real-world results! In Python Machine Learning Mastery: 65 Scikit-Learn Projects for Building Classification, Regression, and Clustering Models with Datasets, author Leonard Brooks delivers a comprehensive, project-based guide designed to take you from machine learning novice to confident practitioner. Whether you're predicting customer churn, forecasting sales, or uncovering hidden patterns in data, this book equips you with the tools to build robust models using one of Python's most versatile libraries: Scikit-Learn. Dive into the essentials of machine learning-supervised, unsupervised, and reinforcement learning-before tackling 65 practical projects across diverse domains like healthcare, finance, marketing, and more. Each project walks you through the entire workflow: loading real-world datasets, preprocessing data, selecting algorithms (from logistic regression and decision trees to support vector machines and gradient boosting), training models, tuning parameters, and evaluating performance. You'll gain mastery over classification (e.g., spam detection or iris flower species prediction), regression (e.g., house price forecasting), and clustering (e.g., customer segmentation), all while building a portfolio of deployable solutions. What sets this book apart is its focus on actionable learning. No dry theory here-every concept is reinforced with code snippets, datasets you can access, and step-by-step explanations. Advanced topics like ensemble techniques, dimensionality reduction, and model deployment ensure you're ready for professional challenges. Plus, appendices include a Scikit-Learn cheat sheet, dataset sources, and a glossary for quick reference. Perfect for beginners with basic Python knowledge or intermediate learners seeking deeper skills, this book bridges the gap between concepts and application. Whether you're a data analyst, student, developer, or professional in business or tech, you'll emerge with the expertise to solve complex problems, extract insights, and drive data-informed decisions. Start your journey to machine learning mastery today-grab your copy and build models that make an impact!

Full Product Details

Author:   Leonard Brooks
Publisher:   Independently Published
Imprint:   Independently Published
Dimensions:   Width: 15.20cm , Height: 0.70cm , Length: 22.90cm
Weight:   0.186kg
ISBN:  

9798275605556


Pages:   132
Publication Date:   22 November 2025
Audience:   General/trade ,  General
Format:   Paperback
Publisher's Status:   Active
Availability:   Available To Order   Availability explained
We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately.

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