Description
Book Synopsis: Reference text in top universities like Stanford and CambridgeSold 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.
Details
Are you interested in data science but intimidated by the complex mathematics involved? Look no further than Numsense! Data Science for the Layman: No Math Added. This reference text, trusted by top universities like Stanford and Cambridge, is now available in over 85 countries and translated into more than 5 languages. Our promise to you is simple: no math added. We have written this book in layman's terms, providing a gentle introduction to data science and its algorithms. Whether you're a beginner or have some experience in the field, Numsense! offers intuitive explanations, real-world examples, and visuals to help you grasp key concepts without feeling overwhelmed.
In this book, each algorithm has its own dedicated chapter that explains how it works, accompanied by a real-world application example. You'll explore popular concepts such as A/B testing, anomaly detection, association rules, clustering, decision trees and random forests, regression analysis, social network analysis, and neural networks. At the end of each chapter, we provide point summaries to reinforce your understanding, and reference sheets that compare the pros and cons of different algorithms. We also include a glossary list of commonly-used terms for quick and easy reference.
With Numsense!, we aim to give you a practical understanding of data science so that you can leverage its strengths to make better decisions. Whether you're a business professional, student, or simply curious about data science, this book is your gateway to unlocking the power of data. Get your copy today and dive into the fascinating world of data science!
Start your data science journey with Numsense! Data Science for the Layman: No Math Added
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