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Labs completed as part of the online ML course offered by Stanford

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Stanford-ML

Please do not look at this code if you have not completed the labs yet. Do not refer to this repo as "answers". Use the online discussion forum to clear your doubts. Completing the labs yourself will help you a lot more. However, if you've already completed the labs you can refer/suggest here for vectorized implementations of the algorithms.

###Labs completed till now:

Lab 1: Implement Linear Regression to predict profits for a food truck, estimate housing prices in Portland, Oregon.

Lab 2: Implement to Logistic Regression to predict whether a student gets admitted into a university.

Lab 3: Implement OVR Logistic Regression and Neural Networks to recognize handwritten digits.

Lab 4: Implement Neural Networks Backpropogation Algorithm to recognize handwritten digits.

Lab 5: Implement regularized Linear Regression and use it to study models with different bias-variance properties.

Lab 6: Implement SVM to build a spam classifier.

Lab 7: a) Using K-Means for image compression. b) Using PCA for finding low dimensional representation of face-images.

Lab 8: a) Using anomaly detection (Gaussian Model) to detect failing servers on a network. b) Using collaborative filtering to build a recommender system for movies.

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Labs completed as part of the online ML course offered by Stanford

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