Fundamentals of Data Science Part III: Machine Learning - Paperback
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Languages:EnglishPublisher:Cayenne Canyon PressISBN-13:9781941043134ISBN-10:1941043135UPC:9781941043134Book Category:Computers, MathematicsBook Subcategory:Data Science, Probability & StatisticsBook Topic:Machine LearningSize:9.21 x 6.14 x 0.66 inchesWeight:0.9811Product ID:SCFZXERE1A
In Part III of this series, we cover the fundamentals of machine learning, focusing on:
- validation methodology (reprint)
- nearest neighbor, k-means, support vector machines, principal component analysis
- tree-based methods: decision trees, bagging, random forest, boosting, XGBoost
- artificial neural networks and deep learning
- reinforcement learning
The focus is on algorithmic development and programming. We code each technique from scratch in Python, using an object-oriented approach.
Languages:EnglishPublisher:Cayenne Canyon PressISBN-13:9781941043134ISBN-10:1941043135UPC:9781941043134Book Category:Computers, MathematicsBook Subcategory:Data Science, Probability & StatisticsBook Topic:Machine LearningSize:9.21 x 6.14 x 0.66 inchesWeight:0.9811Product ID:SCFZXERE1A
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