Data Science from Scratch: First Principles with Python, Second Edition (Greyscale Indian Edition)

Data Science from Scratch teaches data science by showing how its tools and algorithms work, building them from the ground up in Python. This second edition is updated for Python 3.6. The book holds that learning the subject well means understanding the ideas behind libraries, frameworks and toolkits, not only using them. It is for readers with an aptitude for mathematics and some programming skills. Joel Grus guides them through the math and statistics at the core of the field, then through collecting and cleaning data and the basics of machine learning. This edition has new material on deep learning, statistics and natural language processing.

Why You Should Read?

• Learn the basics of linear algebra, statistics and probability, and when each is used in data science.
• Start with a crash course in Python before moving on to the programming the work needs.
• Implement models such as naïve Bayes, decision trees, neural networks and clustering to see how they work.
• Explore natural language processing, network analysis and databases, alongside collecting, cleaning and manipulating messy data.