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images
images
 
 
README.md
README.md
 
 
environment.yml
environment.yml
 
 
ml_03_Numpy_Noteboo_SusanLi.ipynb
ml_03_Numpy_Noteboo_SusanLi.ipynb
 
 
ml_05a_Matplotlib_Noteboo_SusanLi.ipynb
ml_05a_Matplotlib_Noteboo_SusanLi.ipynb
 
 
ml_05b_Exploring Indicator's Across Countrie_SusanLi.ipynb
ml_05b_Exploring Indicator's Across Countrie_SusanLi.ipynb
 
 
ml_05c_Folium_Noteboo_SusanLi.ipynb
ml_05c_Folium_Noteboo_SusanLi.ipynb
 
 
ml_A Simple Classificatio_SusanLi.ipynb
ml_A Simple Classificatio_SusanLi.ipynb
 
 
ml_Ad Demand Forecast Avit_SusanLi.ipynb
ml_Ad Demand Forecast Avit_SusanLi.ipynb
 
 
ml_Airbnb Listing Toront_SusanLi.ipynb
ml_Airbnb Listing Toront_SusanLi.ipynb
 
 
ml_Airbnb New User Booking_SusanLi.ipynb
ml_Airbnb New User Booking_SusanLi.ipynb
 
 
ml_Airbnb New User Bookings__SusanLi.ipynb
ml_Airbnb New User Bookings__SusanLi.ipynb
 
 
ml_BOW_TFIDF_Xgboost_updat_SusanLi.ipynb
ml_BOW_TFIDF_Xgboost_updat_SusanLi.ipynb
 
 
ml_Build Recommender System in an Hour - Part _SusanLi.ipynb
ml_Build Recommender System in an Hour - Part _SusanLi.ipynb
 
 
ml_CLV_Non_Contractua_SusanLi.ipynb
ml_CLV_Non_Contractua_SusanLi.ipynb
 
 
ml_CLV_Online_Retai_SusanLi.ipynb
ml_CLV_Online_Retai_SusanLi.ipynb
 
 
ml_Classifier Visualizatio_SusanLi.ipynb
ml_Classifier Visualizatio_SusanLi.ipynb
 
 
ml_Click-Through Rate Predictio_SusanLi.ipynb
ml_Click-Through Rate Predictio_SusanLi.ipynb
 
 
ml_Consumer_complaint_SusanLi.ipynb
ml_Consumer_complaint_SusanLi.ipynb
 
 
ml_Customer_Segmentation_Online_Retai_SusanLi.ipynb
ml_Customer_Segmentation_Online_Retai_SusanLi.ipynb
 
 
ml_Customer_Segmentation_Whosal_SusanLi.ipynb
ml_Customer_Segmentation_Whosal_SusanLi.ipynb
 
 
ml_Ease_of_Busines_SusanLi.ipynb
ml_Ease_of_Busines_SusanLi.ipynb
 
 
ml_Employee_Turnove_SusanLi.ipynb
ml_Employee_Turnove_SusanLi.ipynb
 
 
ml_European Soccer Regression Analysis using scikit-lear_SusanLi.ipynb
ml_European Soccer Regression Analysis using scikit-lear_SusanLi.ipynb
 
 
ml_Evaluatio_SusanLi.ipynb
ml_Evaluatio_SusanLi.ipynb
 
 
ml_Hotel Optimize Click-throug_SusanLi.ipynb
ml_Hotel Optimize Click-throug_SusanLi.ipynb
 
 
ml_Hotel recommendatio_SusanLi.ipynb
ml_Hotel recommendatio_SusanLi.ipynb
 
 
ml_Introduction to Data Science in Python - Soccer Data Analysi_SusanLi.ipynb
ml_Introduction to Data Science in Python - Soccer Data Analysi_SusanLi.ipynb
 
 
ml_Introduction to Panda_SusanLi.ipynb
ml_Introduction to Panda_SusanLi.ipynb
 
 
ml_LD_SusanLi.ipynb
ml_LD_SusanLi.ipynb
 
 
ml_Logistic Regression balance_SusanLi.ipynb
ml_Logistic Regression balance_SusanLi.ipynb
 
 
ml_Logistic Regression in Python - Step by Ste_SusanLi.ipynb
ml_Logistic Regression in Python - Step by Ste_SusanLi.ipynb
 
 
ml_Machine Learning for Diabete_SusanLi.ipynb
ml_Machine Learning for Diabete_SusanLi.ipynb
 
 
ml_Mercari Price Suggestion Lightgb_SusanLi.ipynb
ml_Mercari Price Suggestion Lightgb_SusanLi.ipynb
 
 
ml_Movielens Recommender Metric_SusanLi.ipynb
ml_Movielens Recommender Metric_SusanLi.ipynb
 
 
ml_Multi label text classificatio_SusanLi.ipynb
ml_Multi label text classificatio_SusanLi.ipynb
 
 
ml_Multiple Linear Regressio_SusanLi.ipynb
ml_Multiple Linear Regressio_SusanLi.ipynb
 
 
ml_NYC taxi far_SusanLi.ipynb
ml_NYC taxi far_SusanLi.ipynb
 
 
ml_Natural Language Processing of Movie Reviews using nltk_SusanLi.ipynb
ml_Natural Language Processing of Movie Reviews using nltk_SusanLi.ipynb
 
 
ml_Predict hotel bookin_SusanLi.ipynb
ml_Predict hotel bookin_SusanLi.ipynb
 
 
ml_Predict_Bay_Area_Home_Pric_SusanLi.ipynb
ml_Predict_Bay_Area_Home_Pric_SusanLi.ipynb
 
 
ml_Price Elasticity of Deman_SusanLi.ipynb
ml_Price Elasticity of Deman_SusanLi.ipynb
 
 
ml_PySpark_Basic_DataFrame_Operation_SusanLi.ipynb
ml_PySpark_Basic_DataFrame_Operation_SusanLi.ipynb
 
 
ml_Quantile Regressio_SusanLi.ipynb
ml_Quantile Regressio_SusanLi.ipynb
 
 
ml_Recommender Systems - The Fundamental_SusanLi.ipynb
ml_Recommender Systems - The Fundamental_SusanLi.ipynb
 
 
ml_Recursive least square_SusanLi.ipynb
ml_Recursive least square_SusanLi.ipynb
 
 
ml_Regression Diagnostic_SusanLi.ipynb
ml_Regression Diagnostic_SusanLi.ipynb
 
 
ml_Regression Plot_SusanLi.ipynb
ml_Regression Plot_SusanLi.ipynb
 
 
ml_SF_Crime_Text_Classification_PySpar_SusanLi.ipynb
ml_SF_Crime_Text_Classification_PySpar_SusanLi.ipynb
 
 
ml_Simple Linear Regressio_SusanLi.ipynb
ml_Simple Linear Regressio_SusanLi.ipynb
 
 
ml_Softmax functio_SusanLi.ipynb
ml_Softmax functio_SusanLi.ipynb
 
 
ml_Solving A Simple Classification Problem with Pytho_SusanLi.ipynb
ml_Solving A Simple Classification Problem with Pytho_SusanLi.ipynb
 
 
ml_Spark DataFrames Project Exercise_Udem_SusanLi.ipynb
ml_Spark DataFrames Project Exercise_Udem_SusanLi.ipynb
 
 
ml_Supervised Learning - Part I_SusanLi.ipynb
ml_Supervised Learning - Part I_SusanLi.ipynb
 
 
ml_Supervised Learning - Part _SusanLi.ipynb
ml_Supervised Learning - Part _SusanLi.ipynb
 
 
ml_TPOT Mercede_SusanLi.ipynb
ml_TPOT Mercede_SusanLi.ipynb
 
 
ml_Text Classification Kera_SusanLi.ipynb
ml_Text Classification Kera_SusanLi.ipynb
 
 
ml_Text Classification keras_consumer_complaint_SusanLi.ipynb
ml_Text Classification keras_consumer_complaint_SusanLi.ipynb
 
 
ml_Time Series ANN & LSTM VI_SusanLi.ipynb
ml_Time Series ANN & LSTM VI_SusanLi.ipynb
 
 
ml_Time Series Forecasting_SusanLi.ipynb
ml_Time Series Forecasting_SusanLi.ipynb
 
 
ml_Time Series LSTM VI_SusanLi.ipynb
ml_Time Series LSTM VI_SusanLi.ipynb
 
 
ml_Time Series of Price Anomaly Detection Expedi_SusanLi.ipynb
ml_Time Series of Price Anomaly Detection Expedi_SusanLi.ipynb
 
 
ml_Topic Modelin_SusanLi.ipynb
ml_Topic Modelin_SusanLi.ipynb
 
 
ml_Unsupervised Learnin_SusanLi.ipynb
ml_Unsupervised Learnin_SusanLi.ipynb
 
 
ml_Using the Twitter API for Tweet Analysi_SusanLi.ipynb
ml_Using the Twitter API for Tweet Analysi_SusanLi.ipynb
 
 
ml_Weather Data Classification using Decision Tree_SusanLi.ipynb
ml_Weather Data Classification using Decision Tree_SusanLi.ipynb
 
 
ml_Weather Data Clustering using k-Mean_SusanLi.ipynb
ml_Weather Data Clustering using k-Mean_SusanLi.ipynb
 
 
ml_Working with Database_SusanLi.ipynb
ml_Working with Database_SusanLi.ipynb
 
 
ml_Xgboost_bow_tfid_SusanLi.ipynb
ml_Xgboost_bow_tfid_SusanLi.ipynb
 
 
ml_Zakka_Canada_CL_SusanLi.ipynb
ml_Zakka_Canada_CL_SusanLi.ipynb
 
 
ml_a_tfstar_SusanLi.ipynb
ml_a_tfstar_SusanLi.ipynb
 
 
ml_assignment01_pandas_uci_adult_mlcourseai.ipynb
ml_assignment01_pandas_uci_adult_mlcourseai.ipynb
 
 
ml_assignment02_analyzing_cardiovascular_desease_data_mlcourseai.ipynb
ml_assignment02_analyzing_cardiovascular_desease_data_mlcourseai.ipynb
 
 
ml_assignment03_decision_trees_mlcourseai.ipynb
ml_assignment03_decision_trees_mlcourseai.ipynb
 
 
ml_assignment04_linreg_optimization_mlcourseai.ipynb
ml_assignment04_linreg_optimization_mlcourseai.ipynb
 
 
ml_assignment05_logit_rf_credit_scoring_mlcourseai.ipynb
ml_assignment05_logit_rf_credit_scoring_mlcourseai.ipynb
 
 
ml_assignment06_regression_wine_mlcourseai.ipynb
ml_assignment06_regression_wine_mlcourseai.ipynb
 
 
ml_assignment07_unsupervised_learning_mlcourseai.ipynb
ml_assignment07_unsupervised_learning_mlcourseai.ipynb
 
 
ml_assignment08_implement_sgd_regressor_mlcourseai.ipynb
ml_assignment08_implement_sgd_regressor_mlcourseai.ipynb
 
 
ml_assignment09_time_series_mlcourseai.ipynb
ml_assignment09_time_series_mlcourseai.ipynb
 
 
ml_assignment10_flight_delays_kaggle_mlcourseai.ipynb
ml_assignment10_flight_delays_kaggle_mlcourseai.ipynb
 
 
ml_b_estimato_SusanLi.ipynb
ml_b_estimato_SusanLi.ipynb
 
 
ml_breast_cancer_predic_SusanLi.ipynb
ml_breast_cancer_predic_SusanLi.ipynb
 
 
ml_c_batche_SusanLi.ipynb
ml_c_batche_SusanLi.ipynb
 
 
ml_classification_decisiontree_DigitsNumerically.ipynb
ml_classification_decisiontree_DigitsNumerically.ipynb
 
 
ml_classification_decisiontree_LoanLending_TirthajyotiSarkar.ipynb
ml_classification_decisiontree_LoanLending_TirthajyotiSarkar.ipynb
 
 
ml_classification_model_comparision_LoanLending_TirthajyotiSarkar.ipynb
ml_classification_model_comparision_LoanLending_TirthajyotiSarkar.ipynb
 
 
ml_classification_svm_Vanderplas.ipynb
ml_classification_svm_Vanderplas.ipynb
 
 
ml_clustering_AffinityPropagation_TirthajyotiSarkar.ipynb
ml_clustering_AffinityPropagation_TirthajyotiSarkar.ipynb
 
 
ml_clustering_Mean_Shift_Clustering_TirthajyotiSarkar.ipynb
ml_clustering_Mean_Shift_Clustering_TirthajyotiSarkar.ipynb
 
 
ml_create_dataset_SusanLi.ipynb
ml_create_dataset_SusanLi.ipynb
 
 
ml_d_traineva_SusanLi.ipynb
ml_d_traineva_SusanLi.ipynb
 
 
ml_datapreparation_feature_engineering_feature_selection_mlcourseai.ipynb
ml_datapreparation_feature_engineering_feature_selection_mlcourseai.ipynb
 
 
ml_datapreparation_sklearn.ipynb
ml_datapreparation_sklearn.ipynb
 
 
ml_decisiontree_Guitar Models_Leon van Bokhorst.ipynb
ml_decisiontree_Guitar Models_Leon van Bokhorst.ipynb
 
 
ml_decisiontree_Shannon's Entropy and Information Gain for Decision Trees_Leon van Bokhorst.ipynb
ml_decisiontree_Shannon's Entropy and Information Gain for Decision Trees_Leon van Bokhorst.ipynb
 
 
ml_decisiontree_bikeshare_exercise.ipynb
ml_decisiontree_bikeshare_exercise.ipynb
 
 
ml_decisiontree_classifier_regressor_sklearn.ipynb
ml_decisiontree_classifier_regressor_sklearn.ipynb
 
 
ml_decisiontree_kNN_mlcourseai.ipynb
ml_decisiontree_kNN_mlcourseai.ipynb
 
 

README.md

Machine Learning Examples

A large collection (~160 notebooks) covering classical ML algorithms and data analysis patterns. Content drawn from multiple authors and courses.

Setup

conda env create -f environment.yml
conda activate ml

Content Organization

Files are named ml_<topic>_<source>.ipynb. Key contributor suffixes:

  • _SusanLi — data exploration, Airbnb/ad-demand forecasting, visualization
  • _mlcourseai — structured assignments (pandas → decision trees → regression → time series → Kaggle)
  • _TirthajyotiSarkar — classification comparisons, loan/financial data
  • _Vanderplas — scikit-learn patterns (from Python Data Science Handbook)

Learning Path (recommended order)

  1. Foundations — ml_03_Numpy_Noteboo_SusanLi.ipynb, ml_05a_Matplotlib_Noteboo_SusanLi.ipynb
  2. Classification — ml_assignment03_decision_trees_mlcourseai.ipynb, ml_classification_svm_Vanderplas.ipynb
  3. Regression — ml_assignment04_linreg_optimization_mlcourseai.ipynb, ml_assignment06_regression_wine_mlcourseai.ipynb
  4. Unsupervised — ml_assignment07_unsupervised_learning_mlcourseai.ipynb
  5. Time Series — ml_assignment09_time_series_mlcourseai.ipynb
  6. End-to-end projects — Airbnb, Ad Demand, Credit Scoring notebooks

Data

Raw datasets live in the data/ subdirectory.