Machine Learning Course Description
- Introduction to Machine Learning
- Supervised Learning and Linear Regression
- Classification and Logistic Regression
- Decision Tree and Random Forest
- Naïve Bayes and Support Vector Machine (self paced)
- Unsupervised Learning
- Basic and frequently used algorithmic techniques including sorting, searching, greedy algorithms and dynamic programming Copy
- Introduction to Deep Learning
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