├── .gitignore ├── LICENSE ├── README.md ├── data ├── FDIC_ Failed Bank List.htm ├── Ontario_energy_demand_2003-2016.csv.gz ├── australian_credit.csv ├── banknotes.csv ├── churn.csv ├── dpc-covid19-ita-regioni.csv ├── gdp.json ├── geoloc_elev.csv ├── housing-data.csv ├── iris.csv ├── isp_data.csv ├── ita-eng.zip ├── rotten_tomatoes_negative_reviews.txt.gz ├── rotten_tomatoes_positive_reviews.txt.gz ├── sms.tsv ├── time_series_covid19_confirmed_US.csv ├── time_series_covid19_confirmed_global.csv ├── titanic-train.csv ├── weight-height.csv ├── wifi_location.csv └── wikipedia_languages.csv ├── notebooks ├── Attention_with_Keras.ipynb ├── Bag_of_Words_Features_for_Text.ipynb ├── Classification_with_Scikit_Learn.ipynb ├── Clustering_with_Scikit_Learn.ipynb ├── Convolutional_Neural_Networks.ipynb ├── Data_Augmentation.ipynb ├── Data_Manipulation_with_Pandas.ipynb ├── Feature_Engineering_with_Scikit_Learn.ipynb ├── Gradient_Boosting_with_XGBoost_and_LightGBM.ipynb ├── Hyperparameter_tuning.ipynb ├── Image_Classification.ipynb ├── Image_Search.ipynb ├── Intro_to_Python_1.ipynb ├── Intro_to_Python_2.ipynb ├── Introduction_to_Deep_Learning_with_Keras.ipynb ├── Keras_Functional_API_and_Model_Inspection.ipynb ├── Machine_Learning_with_Scikit_Learn.ipynb ├── Machine_Translation_with_Recurrent_Neural_Networks.ipynb ├── Model_Evaluation_and_Dimensionality_Reduction_with_Scikit_Learn.ipynb ├── Model_Serving_with_Flask.ipynb ├── Natural_Language_Processing.ipynb ├── Neural_Networks_with_Keras.ipynb ├── Pandas_Matplotlib_Seaborn.ipynb ├── Pre-trained_Models.ipynb ├── Python_Quick_Recap.ipynb ├── Real_World_ML_Ads_Classification.ipynb ├── Real_World_ML_Car_Prices_Regression.ipynb ├── Regression_with_Scikit_Learn.ipynb ├── Sentiment_Classification_with_Recurrent_Neural_Networks.ipynb ├── The_Power_of_TensorFlow.ipynb ├── Time_Series_Forecasting.ipynb ├── Transfer_Learning.ipynb ├── Word_Embeddings.ipynb └── Word_Embeddings_with_Gensim.ipynb ├── solutions_do_not_open ├── Attention_with_Keras_solution.ipynb ├── Bag_of_Words_Features_for_Text_solution.ipynb ├── Classification_with_Scikit_Learn_solution.ipynb ├── Clustering_with_Scikit_Learn_solution.ipynb ├── Convolutional_Neural_Networks_solution.ipynb ├── Data_Augmentation_solution.ipynb ├── Data_Manipulation_with_Pandas_solution.ipynb ├── Feature_Engineering_with_Scikit_Learn_solution.ipynb ├── Gradient_Boosting_with_XGBoost_and_LightGBM_solution.ipynb ├── Hyperparameter_tuning_solution.ipynb ├── Image_Classification_solution.ipynb ├── Image_Search_solution.ipynb ├── Intro_to_Python_1_solution.ipynb ├── Intro_to_Python_2_solution.ipynb ├── Introduction_to_Deep_Learning_with_Keras_solution.ipynb ├── Keras_Functional_API_and_Model_Inspection_solution.ipynb ├── Machine_Learning_with_Scikit_Learn_solution.ipynb ├── Machine_Translation_with_Recurrent_Neural_Networks_solution.ipynb ├── Model_Evaluation_and_Dimensionality_Reduction_with_Scikit_Learn_solution.ipynb ├── Model_Serving_with_Flask_solution.ipynb ├── Natural_Language_Processing_solution.ipynb ├── Neural_Networks_with_Keras_solution.ipynb ├── Pandas_Matplotlib_Seaborn_solution.ipynb ├── Pre-trained_Models_solution.ipynb ├── Python_Quick_Recap_solution.ipynb ├── README.md ├── Real_World_ML_Ads_Classification_solution.ipynb ├── Real_World_ML_Car_Prices_Regression_solution.ipynb ├── Regression_with_Scikit_Learn_solution.ipynb ├── Sentiment_Classification_with_Recurrent_Neural_Networks_solution.ipynb ├── The_Power_of_TensorFlow_solution.ipynb ├── Time_Series_Forecasting_solution.ipynb ├── Transfer_Learning_solution.ipynb ├── Word_Embeddings_solution.ipynb └── Word_Embeddings_with_Gensim_solution.ipynb └── tests └── test_nb.py /.gitignore: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zerotodeeplearning/ztdl-masterclasses/HEAD/.gitignore -------------------------------------------------------------------------------- /LICENSE: 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