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Getting Started with scikit-learn: Learn to Train Machine Learning Models
Getting Started with scikit-learn
is the ultimate beginner-friendly guide to understanding and applying machine learning using one of Python’s most powerful libraries — scikit-learn. Whether you’re a data enthusiast, a student, or an aspiring AI engineer, this book helps you go from zero to building your own intelligent models.
Inside, you’ll
The fundamentals of machine learning concepts — supervised and unsupervised learning, model evaluation, and cross-validation.
How to use scikit-learn’s core modules for regression, classification, and clustering.
Building, training, and fine-tuning models such as Linear Regression, Decision Trees, Random Forests, and SVMs.
Data preprocessing, feature engineering, and handling real-world datasets with NumPy and pandas.
Step-by-step projects and exercises to apply what you’ve learned.
Each chapter focuses on hands-on implementation, helping you understand why algorithms work, not just how to code them.
By the end of this book, you’ll have the confidence to design and deploy your own machine learning workflows — all within the simple, elegant ecosystem of Python + scikit-learn.
Perfect
Students and beginners in AI or Data Science
Python developers exploring ML for the first time
Anyone who wants a practical, code-driven introduction to machine learning
Inside, you’ll
The fundamentals of machine learning concepts — supervised and unsupervised learning, model evaluation, and cross-validation.
How to use scikit-learn’s core modules for regression, classification, and clustering.
Building, training, and fine-tuning models such as Linear Regression, Decision Trees, Random Forests, and SVMs.
Data preprocessing, feature engineering, and handling real-world datasets with NumPy and pandas.
Step-by-step projects and exercises to apply what you’ve learned.
Each chapter focuses on hands-on implementation, helping you understand why algorithms work, not just how to code them.
By the end of this book, you’ll have the confidence to design and deploy your own machine learning workflows — all within the simple, elegant ecosystem of Python + scikit-learn.
Perfect
Students and beginners in AI or Data Science
Python developers exploring ML for the first time
Anyone who wants a practical, code-driven introduction to machine learning
179 pages, Kindle Edition
Published October 26, 2025
2 people want to read
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October 27, 2025
I got this book for my CS class and oh! boy this is awesome!
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