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Assignments completed for my Machine Learning course: Topics include probability and statistics proofs, MLE/MAP parameter estimation, EM Algorithm, Bayes Theorem implementations, gradient descent methods, Neural Networks and Deep Learning.

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Assignments completed for my Machine Learning course: Topics include probability and statistics proofs, MLE/MAP parameter estimation, EM Algorithm, Bayes Theorem implementations, gradient descent methods, Neural Networks and Deep Learning.

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machine-learning deep-neural-networks deep-learning svm linear-regression naive-bayes-classifier pca logistic-regression gradient-descent parameter-estimation bayesian-optimization em-algorithm statistical-models probabilistic-models map-estimation mle-estimation k-means-clustering

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