01 - Introduction
02 - 1. Introduction to Data Science
03 - 2. Introduction to Machine Learning
04 - 3. Regression Models
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02 - Multiple linear regression (8:36)
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01 - Linear regression (11:18)
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03 - Logistic regression Concepts (8:48)
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04 - Logistic regression Data preparation (7:05)
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05 - Logistic regression Treat missing values (9:32)
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06 - Logistic regression Re-encode variables (11:01)
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07 - Logistic regression Validating data set (3:22)
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08 - Logistic regression Model deployment (4:18)
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09 - Logistic regression Model evaluation (2:30)
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10 - Logistic regression Test prediction (3:42)
05 - 4. Clustering Models
06 - 5. Dimension Reduction Methods
07 - 6. Other Popular Machine Learning Methods
08 - Conclusion
