Numsense! Data Science for the Layman by Kenneth Soo

Numsense! Data Science for the Layman by Kenneth Soo

Used in Stanford's CS102 Big Data (Spring 2017) course.

Want to get started on data science?
Our promise: no math added.

This book has been written in layman's terms as a gentle introduction to data science and its algorithms. Each algorithm has its own dedicated chapter that explains how it works, and shows an example of a real-world application. To help you grasp key concepts, we stick to intuitive explanations, as well as lots of visuals, all of which are colorblind-friendly.

Popular concepts covered include:

• A/B Testing
• Anomaly Detection
• Association Rules
• Clustering
• Decision Trees and Random Forests
• Regression Analysis
• Social Network Analysis
• Neural Networks

Features:

• Intuitive explanations and visuals
• Real-world applications to illustrate each algorithm
• Point summaries at the end of each chapter
• Reference sheets comparing the pros and cons of algorithms
• Glossary list of commonly-used terms

With this book, we hope to give you a practical understanding of data science, so that you, too, can leverage its strengths in making better decisions.