Numsense! Data Science for the Layman: No Math Added

Condition - Very Good
The item shows wear from consistent use, but it remains in good condition and functions properly. Item may arrive with damaged packaging or be repackaged. It may be marked, have identifying markings on it, or have minor cosmetic damage. It may also be missing some parts/accessories or bundled items.

Numsense! Data Science for the Layman: No Math Added

----------------------------------------
Reference text for data science in top universities like Stanford and Cambridge.
Sold in over 85 countries and 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.
Country USA
Binding Kindle Edition
Edition 1
EISBN 9789811127007
Format Kindle eBook
IsAdultProduct 0
NumberOfPages 147
PublicationDate 2017-02-03
ReleaseDate 2017-02-03

Country	USA
Binding	Kindle Edition
Edition	1
EISBN	9789811127007
Format	Kindle eBook
IsAdultProduct	0
NumberOfPages	147
PublicationDate	2017-02-03
ReleaseDate	2017-02-03

Numsense! Data Science for the Layman: No Math Added

You might also like...