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) Introduction
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Classroom Contents
Data Science Hands-On Crash Course
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- 1 ) Introduction
- 2 ) Setup
- 3 ) Linear regression (theory)
- 4 ) Linear regression (Python)
- 5 ) Classification (theory)
- 6 ) Classifiaction (Python)
- 7 ) Resampling & regularization (theory)
- 8 ) Resampling and regularization (Python)
- 9 ) Decision trees (theory)
- 10 ) Decision trees (Python)
- 11 ) SVM (theory)
- 12 ) SVM (Python)
- 13 ) Unsupervised learning (theory)
- 14 ) Unsupervised learning (Python)
- 15 ) Conclusion
