Data Science from Scratch: First Principles with Python
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Step-by-step implementations of core data science algorithms from scratch for deep understanding
Updated for Python 3.6 with new content on deep learning, statistics, and NLP
Comprehensive crash course in Python, linear algebra, statistics, and probability
Hands-on projects including machine learning, recommender systems, and NLP applications
Guidance on data collection, cleaning, and analysis for real-world data science tasks
Summarized by Shop
To really learn data science, you should not only master the tools―data science libraries, frameworks, modules, and toolkits―but 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.