├── LICENSE ├── README.md ├── dss-2016 ├── README.md ├── churn_prediction │ ├── README.md │ ├── churn-tutorial-explore-explain.ipynb │ ├── churn-tutorial.ipynb │ └── user-activity-data.ipynb ├── deep_learning │ ├── Deep_Learning_for_Image_Analysis.ipynb │ └── README.md ├── lead_scoring │ ├── README.md │ └── lead_scoring_tutorial.ipynb └── recommendation_systems │ ├── README.md │ ├── Recommender DeepDive - Part 1.ipynb │ ├── Recommender DeepDive - Part 2.ipynb │ ├── book-recommender-exercises.ipynb │ └── book-recommender-solutions.ipynb ├── notebooks ├── AnyGivenSunday.ipynb ├── airline_on-time_performance.ipynb ├── autotagging_hacker_news_posts.ipynb ├── bank_lead_scoring_demo.ipynb ├── basic_recommender_functionalities.ipynb ├── build_imagenet_deeplearning.ipynb ├── customer-churn-prediction.ipynb ├── data_mining_web_session_logs.ipynb ├── datapipeline_recsys_intro.ipynb ├── datas_messy_clean_it.ipynb ├── deep_text_learning.ipynb ├── deploy-scikit-learn-in-ps.ipynb ├── feature-engineering.ipynb ├── feature_engineering_with_graphlab_create.ipynb ├── five_line_recommender.ipynb ├── follow_the_cryptocurrency.ipynb ├── food_retrieval-public.ipynb ├── fraud-detection.ipynb ├── getting_started_with_graphlab_create.ipynb ├── getting_started_with_python.ipynb ├── graph_analytics_movies.ipynb ├── image_similarity.ipynb ├── intro-regression.ipynb ├── introduction_to_sframes.ipynb ├── kaggle_bike_share_prediction.ipynb ├── linear_regression_benchmark.ipynb ├── link_prediction.ipynb ├── machine_learning_with_graphLab_create.ipynb ├── model_parameter_search.ipynb ├── predictive_services_intro.ipynb ├── product_matching.ipynb ├── reading_data_from_impala.ipynb ├── recsys_explicit_rating.ipynb ├── recsys_rank_10K_song.ipynb ├── reddit_analysis.ipynb ├── sentiment_classifier.ipynb ├── sherlock_text_analytics.ipynb └── spark_and_graphlab_create.ipynb ├── strata-nyc-2015 ├── README.md ├── deep-learning │ ├── Deep Learning for Image Classification and Finding Similar Images.ipynb │ ├── image_similarity.ipynb │ └── images │ │ ├── AA1.png │ │ ├── alexnet.png │ │ ├── cifar.png │ │ ├── evaluate.png │ │ ├── extract_features.png │ │ ├── improve.png │ │ ├── linear.png │ │ ├── load.png │ │ ├── quadratic.png │ │ ├── spiral.1-2.2-2-2-2-2-2.jpg │ │ ├── train.png │ │ ├── workflow1.png │ │ ├── workflow2.png │ │ ├── workflow3.png │ │ └── workflow4.png ├── deployment │ ├── images │ │ ├── left.png │ │ ├── middle.png │ │ ├── predictive_services_overview.png │ │ └── right.png │ ├── predictive_services.ipynb │ └── scikit_deployment.ipynb ├── feature_engineering │ ├── Feature Engineering for Text Data.ipynb │ └── PCA demo.ipynb └── recommendation-systems │ ├── README.md │ ├── Recommender DeepDive - Part 1.ipynb │ ├── Recommender DeepDive - Part 2.ipynb │ ├── book-recommender-exercises.ipynb │ ├── book-recommender-solutions.ipynb │ ├── strata-nyc-2015-recommendation-systems.key │ └── strata-nyc-2015-recommendation-systems.pptx ├── strata-sj-2016 ├── README.md ├── deep-learning │ ├── Deep Learning for Image Classification and Finding Similar Images.ipynb │ ├── Strata-SJ-2016-Deeplearning.pptx │ ├── image_similarity.ipynb │ └── images │ │ ├── AA1.png │ │ ├── alexnet.png │ │ ├── cifar.png │ │ ├── evaluate.png │ │ ├── extract_features.png │ │ ├── improve.png │ │ ├── linear.png │ │ ├── load.png │ │ ├── quadratic.png │ │ ├── spiral.1-2.2-2-2-2-2-2.jpg │ │ ├── train.png │ │ ├── workflow1.png │ │ ├── workflow2.png │ │ ├── workflow3.png │ │ └── workflow4.png ├── intro-ml │ ├── getting-started-with-sframes.ipynb │ └── sentiment_analysis.ipynb ├── ml-in-production │ ├── deploy-dress-recommender.ipynb │ ├── deploy-scikit-learn.ipynb │ ├── images │ │ ├── left.png │ │ ├── middle.png │ │ ├── predictive_services_overview.png │ │ └── right.png │ └── ml-production.key ├── recommendation-systems │ ├── README.md │ ├── Recommender DeepDive - Part 1.ipynb │ ├── Recommender DeepDive - Part 2.ipynb │ ├── book-recommender-exercises.ipynb │ ├── 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