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Data Science from Scratch: First Principles with Python,Used
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To really learn data science, you should not only master the toolsdata science libraries, frameworks, modules, and toolkitsbut also understand the ideas and principles underlying them. Updated for Python 3.6, this second edition of Data Science from Scratch shows you how these tools and algorithms work by implementing them from scratch.If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with the hacking skills you need to get started as a data scientist. Packed with new material on deep learning, statistics, and natural language processing, this updated book shows you how to find the gems in today?s messy glut of data. Get a crash course in Python Learn the basics of linear algebra, statistics, and probabilityand how and when they?re used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as knearest neighbors, Na?ve Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases
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- Q: What topics are covered in 'Data Science from Scratch'? A: The book covers foundational topics in data science including linear algebra, statistics, probability, machine learning algorithms, deep learning, natural language processing, and data manipulation techniques.
- Q: Is this book suitable for beginners in data science? A: Yes, 'Data Science from Scratch' is designed for readers with an aptitude for mathematics and some programming skills, making it accessible for beginners eager to learn data science concepts.
- Q: What programming language is used in this book? A: The book employs Python, specifically updated for Python 3.6, to demonstrate data science concepts and implement algorithms from scratch.
- Q: How many pages does 'Data Science from Scratch' have? A: The book contains 403 pages, providing a comprehensive overview of data science principles and practices.
- Q: Who is the author of 'Data Science from Scratch'? A: The author of the book is Joel Grus, a knowledgeable figure in the field of data science.
- Q: What is the binding type of this book? A: This edition of 'Data Science from Scratch' is available in paperback binding.
- Q: When was 'Data Science from Scratch' published? A: The book was published on June 11, 2019.
- Q: Does the book include practical examples? A: Yes, the book includes practical examples that demonstrate how to implement various data science algorithms and tools.
- Q: What is the edition of this book? A: This is the second edition of 'Data Science from Scratch'.
- Q: Can this book help with understanding machine learning? A: Yes, it provides fundamental insights into machine learning, including how to implement models such as decision trees and neural networks.