Silver Blog, Apr 2017Data Science for the Layman (No Math Added)

Written for the layman, this book is a practical yet gentle introduction to data science. Discover key concepts behind more than 10 classic algorithms, explained with real-world examples and intuitive visuals.

By Annalyn Ng (University of Cambridge) and Kenneth Soo (Stanford University).

Want to get started on data science? Or just fancy a good read?

Numsense! Data Science for the Layman is an introductory data science book for readers without a background in statistics or computer science. It steers clear of jargon to present key algorithms in a simple and succinct manner. To help you along, each algorithm is also illustrated with real-world examples and intuitive visuals.

Our promise: no math added.


Discover key concepts for over 10 classic algorithms and methods, including:

  • A/B Testing
  • Anomaly Detection
  • Association Rules
  • Clustering
  • Decision Trees and Random Forests
  • Regression Analysis
  • Social Network Analysis
  • Neural Networks

To help you revise what you’ve learned, we’ve also included:

  • Cheat sheets comparing pros & cons of algorithms
  • End-chapter summaries
  • Glossary list of commonly-used terms

Who is this book for?

You! But really, anyone interested in data science – be it a business manager supervising analysts, consultants searching for new insights in data, students entering into this field, or anyone with a curious mind.

Why should I be interested in data science?

You’ve seen how data science has revolutionized the way we live and work. Google uses it to generate relevant results to your search queries and Amazon uses it to recommend products you might like. Recently, data science algorithms have also been used to drive the development of digital personal assistants and autonomous vehicles. Understanding how these algorithms work is crucial to appreciating its potential impact on our future.

How will reading this book add value to my work?

Data science algorithms can be applied in a wide range of fields – whether for customer profiling or medical diagnosis, these algorithms can give you key insights to help you make more strategic decisions.

What do others have to say?

"... Having been familiar with the work of Annalyn Ng and Kenneth Soo for some time, it comes as no surprise that the book delivers on its titular promise. This is data science for the layman, and the often-complex math -- which the book describes at a high level -- is intentionally not covered in detail. But don't be misled: this does not mean that the contents are in any way watered down. In fact, the information contained within is robust, with its strength being that it is abridged and concise."

Data Scientist and Deputy Editor of KDnuggets

"... Numsense!  is a convenient graphical description of key data science algorithms, useful as an introduction for new data scientists, an overview for business people who work with analysts, or a stimulating read for anyone who wants to know what happens to their data."

Deputy Director of The Psychometrics Centre,
Lecturer in Big Data Analytics and Quantitative Social Science,
Cambridge University Judge Business School