Reference text in top universities like Stanford and Cambridge Sold in over 85 countries, translated into more than 5 languages
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
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.
Description:
Reference text in top universities like Stanford and Cambridge
Sold in over 85 countries, translated into more than 5 languages
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:
Features:
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.