- Want to get started on data science?
- 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.
- 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.
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…
Continue reading “Book: Data Science for the Layman: No Math Added”
- Lab: Model Selection Using Cross-Validation (5:32)
- Lab: Forward Stepwise Selection and Model Selection Using Validation Set (10:32)
- Chapter 7: Moving Beyond Linearity ( slides , playlist )
- Lab: Random Forests and Boosting (15:35)
- Multiple Linear Regression and Interpreting Regression Coefficients (15:38)
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@KirkDBorne: “In-depth #MachineLearning in 15 hours of expert videos: #BigData #DataScience by @Rbloggers”
In January 2014, Stanford University professors Trevor Hastie and Rob Tibshirani (authors of the legendary Elements of Statistical Learning textbook) taught an
In-depth introduction to machine learning in 15 hours of expert videos