eTEXT

Machine Learning Hero

Master Data Science with Python Essentials

By: Cuantum Technologies LLC

Write A Review

eText | 17 January 2025 | Edition Number 1

At a Glance

Format
ePUB

eText

$68.19

or 4 interest-free payments of $17.05 with

or

OR

Free with Kobo Plus Read

Start Free Trial *

Subscribe and read all you want.
$13.99 a month after free trial. Cancel Anytime. Learn more.

Instant online reading in your Booktopia eTextbook Library *

Read online on

Desktop

Tablet

Mobile

Not downloadable to your eReader or an app

Learn machine learning through hands-on Python projects, covering core concepts, essential libraries, and real-world applications for aspiring data scientists.

Key Features

Comprehensive coverage of machine learning fundamentals and advanced topics
Real-world projects to apply skills in practical scenarios
Integration of Python libraries for data science and AI development

Book Description

This book takes you on a journey through the world of machine learning, beginning with foundational concepts such as supervised and unsupervised learning, and progressing to advanced topics like feature engineering, hyperparameter tuning, and dimensionality reduction. Each chapter blends theory with practical exercises to ensure a deep understanding of the material. The book emphasizes Python, introducing essential libraries like NumPy, Pandas, Matplotlib, and Scikit-learn, along with deep learning frameworks like TensorFlow and PyTorch. You'll learn to preprocess data, visualize insights, and build models capable of tackling complex datasets. Hands-on coding examples and exercises reinforce concepts and help bridge the gap between knowledge and application. In the final chapters, you'll work on real-world projects like predictive analytics, clustering, and regression. These projects are designed to provide a practical context for the techniques learned and equip you with actionable skills for data science and AI roles. By the end, you'll be prepared to apply machine learning principles to solve real-world challenges with confidence.

What you will learn

Build machine learning models using Python libraries
Apply feature engineering and preprocessing techniques
Visualize datasets with Matplotlib and Seaborn
Optimize machine learning models with hyperparameter tuning
Implement clustering and dimensionality reduction methods
Work on real-world projects for practical experience

Who this book is for

Aspiring data scientists, software developers, and tech enthusiasts seeking to master machine learning concepts and Python libraries. Basic Python knowledge is recommended but not required, as foundational topics are covered.