University-of-Washington-Machine-Learning-Specialization

These are the assignments and practice done during the University of Washington's Machine Learning Specialization course. The files were available in Turicreate and was done using Google Colaboratory and then moved here.

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University-of-Washington-Machine-Learning-Specialization

These are the assignments and practice done during the University of Washington's Machine Learning Specialization course. The files were available in Turicreate and was done using Google Colaboratory and then moved here.

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Name		Name	Last commit message	Last commit date
Latest commit History 41 Commits
README.md		README.md
Week_01-Getting_Started_with_SFrames.ipynb		Week_01-Getting_Started_with_SFrames.ipynb
Week_02-Predicting_House_Prices.ipynb		Week_02-Predicting_House_Prices.ipynb
Week_03-Sentiment_Analysis.ipynb		Week_03-Sentiment_Analysis.ipynb
Week_04-Document_retrieval.ipynb		Week_04-Document_retrieval.ipynb
Week_06-Image_Classification_with_Deep_Features.ipynb		Week_06-Image_Classification_with_Deep_Features.ipynb
Week_06-Image_Retrieval_using_Deep_Features.ipynb		Week_06-Image_Retrieval_using_Deep_Features.ipynb
Week_07-PhillyCrime.ipynb		Week_07-PhillyCrime.ipynb
Week_07-Regression_Simple_Linear_Regression.ipynb		Week_07-Regression_Simple_Linear_Regression.ipynb
Week_08-Numpy_tutorial.ipynb		Week_08-Numpy_tutorial.ipynb
Week_08-Regression-Multiple Regression (Interpretation).ipynb		Week_08-Regression-Multiple Regression (Interpretation).ipynb
Week_08-Regression-Multiple Regression (gradient descent).ipynb		Week_08-Regression-Multiple Regression (gradient descent).ipynb
Week_09-Regression-Polynomial_Regression(Assessing Fit).ipynb		Week_09-Regression-Polynomial_Regression(Assessing Fit).ipynb
Week_10-Assignment1_Observing_effects_of_L2_penalty_in_polynomial_regression.ipynb		Week_10-Assignment1_Observing_effects_of_L2_penalty_in_polynomial_regression.ipynb
Week_10-Assignment2_Implementing_ridge_regression_via_gradient_descent.ipynb		Week_10-Assignment2_Implementing_ridge_regression_via_gradient_descent.ipynb
Week_10-Overfitting_Demo_Ridge_Lasso.ipynb		Week_10-Overfitting_Demo_Ridge_Lasso.ipynb
Week_11-Assignment2_Implementing_LASSO_using_coordinate_descent.ipynb		Week_11-Assignment2_Implementing_LASSO_using_coordinate_descent.ipynb
Week_11-Assignment_1_Using_LASSO_to_select_features.ipynb		Week_11-Assignment_1_Using_LASSO_to_select_features.ipynb
Week_12-Predicting_house_prices_using_k_nearest_neighbors_regression.ipynb		Week_12-Predicting_house_prices_using_k_nearest_neighbors_regression.ipynb
Week_13-Predicting_sentiment_from_product_reviews.ipynb		Week_13-Predicting_sentiment_from_product_reviews.ipynb
Week_14-A1_Implementing_logistic_regression_from_scratch.ipynb		Week_14-A1_Implementing_logistic_regression_from_scratch.ipynb
Week_15-A1_Identifying_safe_loans_with_decision_trees.ipynb		Week_15-A1_Identifying_safe_loans_with_decision_trees.ipynb
Week_15-A2_Implementing_binary_decision_trees.ipynb		Week_15-A2_Implementing_binary_decision_trees.ipynb
Week_16-A1_Decision_Trees_in_Practice.ipynb		Week_16-A1_Decision_Trees_in_Practice.ipynb
Week_16-A2_Boosting_a_decision_stump.ipynb		Week_16-A2_Boosting_a_decision_stump.ipynb
Week_17-A1_Exploring_Ensemble_Methods.ipynb		Week_17-A1_Exploring_Ensemble_Methods.ipynb
Week_19-Training_Logistic_Regression_via_Stochastic_Gradient_Ascent.ipynb		Week_19-Training_Logistic_Regression_via_Stochastic_Gradient_Ascent.ipynb
Week_21-A1_Choosing_features_and_metrics_for_Nearest_Neighbor_search.ipynb		Week_21-A1_Choosing_features_and_metrics_for_Nearest_Neighbor_search.ipynb
Week_21-A2_1NN_Implementing_Locality_Sensitive_Hashing.ipynb		Week_21-A2_1NN_Implementing_Locality_Sensitive_Hashing.ipynb
Week_22-Clustering_text_data_with_k_means.ipynb		Week_22-Clustering_text_data_with_k_means.ipynb
Week_23-A1_Fitting_Gaussian_Mixture_Models_with_EM.ipynb		Week_23-A1_Fitting_Gaussian_Mixture_Models_with_EM.ipynb
Week_23-A2_Clustering_Text_Data_with_Gaussian_Mixtures.ipynb		Week_23-A2_Clustering_Text_Data_with_Gaussian_Mixtures.ipynb
Week_24-Modelling_Text_Topics_with_Latent_Dirichlet_Allocation.ipynb		Week_24-Modelling_Text_Topics_with_Latent_Dirichlet_Allocation.ipynb
Week_25-Modelling_Text_Data_with_a_Hierarchy_of_Clusters.ipynb		Week_25-Modelling_Text_Data_with_a_Hierarchy_of_Clusters.ipynb

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University-of-Washington-Machine-Learning-Specialization

These are the assignments and practice done during the University of Washington's Machine Learning Specialization course. The files were available in Turicreate and was done using Google Colaboratory and then moved here.

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