Advanced Machine Learning Course (3rd Batch)

1. Math for ML (3 lectures)
---> 3 Lectures

Supervised Learning:
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2. Theory of Linear Regression. (2 lectures)
3. Predict housing prices using Linear regression.(1 lecture)
4. Theory of Logistic Regression. (1 lecture)
5. Heart Disease Prediction using Logistic Regression. (1 lecture)
6. Overfitting and Regularization. (1 lecture)
7. Decision Trees. (2 lectures)
8. Rain prediciton. (1 lecture)
---> 9 lectures

Deep Learning:
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9. Artificial Neural Networks theory. (2 lectures)
10. ANN training. (1 lecture)
11. Image classification using deep neural nets. (1 lecture)
---> 4 lectures

Practical Advice for Machine Learning:
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12. Evaluating model, model selection, bias, variance.(2 lecture)
13. ML development process and error analysis. (2 lecture)
---> 4 lectures

Unsupervised Learning:
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14. K-means clustering Algorithm. (1 lecture)
15. Customer Segmentation using K-Means Clustering. (1 lecture)
16. Anomaly Detection Algortihm. (1 lecture)
17. Credit card fraud detection. (1 lecture)
18. Principal Component Analysis. (1 lecture)
19. PCA implementation. (1 lecture)
---> 6 lectures

Recommender Systems:
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20. Collaborative filtering.(1 lecture)
21. Content-based fitering.(1 lecture)
22. Deep learning for recommender systems. (1 lecture)
23. Movie recommendation system.(1 lecture)
---> 4 lectures

---> total 30 lectures