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Cover for Machine Learning with Python for Beginners: A Beginner’s Journey into Data Science and AI

Machine Learning with Python for Beginners: A Beginner’s Journey into Data Science and AI

Durée
3h 44min
Langue
Anglais
Format
Catégorie

Documents et essais

Dive into the world of machine learning with "Machine Learning with Python for Beginners," a comprehensive guide designed to introduce you to the fundamentals of machine learning using Python. This accessible book equips beginners with the essential tools and knowledge needed to embark on practical machine learning projects.

From setting up your Python environment to exploring advanced algorithms, this book covers a broad spectrum of topics including supervised and unsupervised learning, data handling, visualization, and even neural networks and deep learning. Each chapter is crafted to build upon the previous one, ensuring a structured and engaging learning path.

What sets this book apart is its focus on practical implementation. You'll not only learn about the theories and concepts that underpin machine learning but also apply them through exciting projects, such as predicting house prices, classifying emails, recognizing images, and customer segmentation. These projects are designed to solidify your understanding and inspire you to apply machine learning to problems you're passionate about.

"Machine Learning with Python for Beginners" is perfect for:

• Beginners to programming or those new to machine learning. • Intermediate programmers who want to solidify their understanding of machine learning fundamentals. • Educators and students looking for a resource-rich, accessible introduction to machine learning.

Featuring tips on best practices, staying current with trends, and resources for deeper exploration, this book is your first step towards mastering machine learning with Python. Join us on this educational journey and start transforming data into actionable insights today!

© 2024 Brandon Scott (Livre audio): 9798882206801

Date de publication

Livre audio : 1 mai 2024

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