This book is for aspiring data science professionals who are familiar with Python & R and have some statistics background. Those developers who are currently implementing 1 or 2 data science algorithms and now want to learn more to expand their skill will find this book quite useful.
- Preface
- Classification Using K Nearest Neighbors
- Naive Bayes
- Decision Trees
- Random Forest
- Clustering into K Clusters
- Regression
- Time Series Analysis
- Statistics
- R Reference
- Python Reference
- Glossary of Algorithms and Methods in Data Science
Who this book is for
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