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Data Science from Scratch: First Principles with Python (Paperback)

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Key item features

Foundational Understanding: Emphasizes learning underlying principles and ideas of data science, not just tools, by implementing them from scratch.
Python Implementation: Updated for Python 3.6, the book guides users in implementing data science tools and algorithms using Python.
Core Concepts: Covers essential mathematics and statistics for data science, including linear algebra, probability, and their practical applications.
Data Handling: Teaches skills for collecting, exploring, cleaning, munging, and manipulating diverse datasets.
Machine Learning: Explores fundamental machine learning concepts and practical implementations of various models like k-nearest neighbors, neural networks, and clustering.
Advanced Topics: Introduces advanced data science areas such as deep learning, natural language processing, recommender systems, and network analysis.

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