Numsense! Data Science for the Layman: No Math Added Book
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 and visuals.
Popular concepts covered include:
– A/B Testing
– Anomaly Detection
– Association Rules
– Decision Trees and Random Forests
– Regression Analysis
– Social Network Analysis
– Neural Networks
– 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.