649: Introduction to Machine Learning
Super Data Science: ML & AI Podcast with Jon Krohn
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Practical Activities in Machine Learning: Regression, Classification, and Clustering
This chapter delves into practical machine learning activities, highlighting examples such as predicting breast cancer tumors, forecasting energy output, and clustering customers based on behavior. It emphasizes the importance of citing datasets, setting appropriate thresholds in classification models, and evaluating false positives and negatives. The chapter also discusses the significance of creating separate training and test datasets, monitoring model performance, feature scaling, and evaluating metrics like accuracy and R squared.
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