Numsense! Data Science for the Layman (No Math Added)
Numsense! Data Science for the Layman (No Math Added) by Annalyn Ng, Kenneth Soo
English | March 24, 2017 | ISBN: 9811110689 | EPUB | 146 pages | 3.4 MB
English | March 24, 2017 | ISBN: 9811110689 | EPUB | 146 pages | 3.4 MB
Used in Stanford's CS102 Big Data 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.