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

ISBN: B0G3Q9W7KS

ISBN13: 9798275605556

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

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

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