Data Science from Scratch: 2nd Edition
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Data Science from Scratch: 2nd Edition
First Principles with Python, 2nd Edition
$33.90
$54.90
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Detailed Overview:
Data Science from Scratch: First Principles with Python, 2nd Edition by Joel Grus is a practical and accessible guide designed for readers who want to understand the foundations of data science through hands-on Python programming. Rather than relying heavily on complex libraries or black-box tools, the book explains how core data science concepts work from the ground up. It introduces essential topics such as statistics, probability, linear algebra, machine learning, data visualization, natural language processing, and deep learning using clear explanations and real coding examples.
The second edition has been updated to reflect modern Python practices and current data science techniques, making it highly valuable for beginners, programmers, analysts, and aspiring machine learning professionals. Readers learn how to build algorithms step by step, gaining a deeper understanding of how models and analytical methods function internally. The book also emphasizes practical implementation, helping readers strengthen both theoretical knowledge and coding skills simultaneously.
Widely appreciated for its conversational writing style and educational approach, this book serves as an excellent resource for self-learners, students, and professionals looking to build a solid foundation in data science and Python programmin 
Product Details:
Title: Data Science from Scratch: First Principles with Python 2nd Edition
Author: Joel Grus
ISBN-13: 978-1492041139
ISBN-10: 1492041130
Publisher: O’Reilly Media
Binding: Paperback
No of Pages: 406
Language: English
Publisher Date: April 12, 2019
Data Science from Scratch: First Principles with Python, 2nd Edition provides a comprehensive introduction to the fundamental concepts behind modern data science. The book focuses on teaching readers how to implement data science techniques manually using Python, helping them understand the logic behind algorithms instead of simply using prebuilt tools. Key topics include data manipulation, probability, statistics, hypothesis testing, machine learning, neural networks, recommendation systems, databases, and visualization.
Joel Grus uses practical examples and easy-to-follow coding exercises to explain complex concepts in a beginner-friendly manner. The book is ideal for programmers, analysts, students, and technology professionals who want to develop strong analytical and problem-solving skills. By combining theory with real-world coding applications, the book helps readers gain confidence in applying data science techniques to practical projects and professional work environments.
Joel Grus is a software engineer, data scientist, and author known for making complex technical subjects approachable and practical. He has worked with leading technology companies and has extensive experience in machine learning, artificial intelligence, and data analysis. Joel Grus is widely recognized for his engaging teaching style and ability to explain advanced programming and data science concepts in a simple, understandable way. His work has helped many beginners and professionals strengthen their Python and data science skills.
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