Used as course material in top universities like Stanford and Cambridge .
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..
To help you grasp key concepts, we stick to intuitive explanations, as well as lots of visuals, all of which are colorblind-friendly.
Each algorithm has its own dedicated chapter that explains how it works, and shows an example of a real-world application.
This book has been written in layman\'s terms as a gentle introduction to Data Science and its algorithms.
Want to get started on Data science? Our promise: no Math added.
Sold in over 85 countries and translated into more than 5 languages .
Used as course material in top universities like Stanford and Cambridge
