Pinned Repositories
amazon-forecast-samples
Notebooks and examples on how to onboard and use various features of Amazon Forecast.
amazon-personalize-samples
Notebooks and examples on how to onboard and use various features of Amazon Personalize
aws-ai-qna-bot
Code samples related to "Creating a Question and Answer Bot with Amazon Lex and Amazon Alexa", published on the AWS AI Blog. QnABot (pronounced “Q and A Bot”), uses Amazon Lex and Amazon Alexa to provide a conversational interface to your “Questions and Answers”, so users can just ask their questions and get quick and relevant answers.
aws-deepracer-workshops
DeepRacer workshop content
beer_recommendations
Joke_predictor
Can you predict if a joke will be funny
mlb-stats-project
scikit-learn-videos
Jupyter notebooks from the scikit-learn video series
state_predictor
tennis_predictions
scbronder's Repositories
scbronder/dsc-0-04-14-missing-data-summary-nyc-career-ds-102218
scbronder/dsc-0-07-18-z-scores-and-p-values-nyc-career-ds-102218
scbronder/dsc-0-09-12-gaussian-distributions-nyc-career-ds-102218
scbronder/dsc-1-04-03-lambda-functions-nyc-career-ds-102218
scbronder/dsc-1-09-19-one-sample-z-test-nyc-career-ds-102218
scbronder/dsc-1-11-04-dealing-with-categorical-variables-nyc-career-ds-102218
scbronder/dsc-2-13-06-reading-erd-diagrams-nyc-career-ds-102218
scbronder/dsc-2-13-07-using-an-orm-nyc-career-ds-102218
scbronder/dsc-2-19-14-sampling-statistics-nyc-career-ds-102218
scbronder/dsc-2-19-15-confidence-intervals-lab-nyc-career-ds-102218
scbronder/dsc-2-19-16-confidence-intervals-with-t-distribution-nyc-career-ds-102218
scbronder/dsc-2-20-01-introduction-nyc-career-ds-102218
scbronder/dsc-2-20-03-introduction-to-experimental-design-nyc-career-ds-102218
scbronder/dsc-2-20-04-p-values-and-null-hypothesis-nyc-career-ds-102218
scbronder/dsc-2-20-09-2-sample-t-tests-lab-nyc-career-ds-102218
scbronder/dsc-2-20-10-type-1-and-type-2-errors-nyc-career-ds-102218
scbronder/dsc-2-20-11type-1-and-type-2-errors-lab-nyc-career-ds-102218
scbronder/dsc-3-27-07-evaluation-metrics-nyc-career-ds-102218
scbronder/dsc-3-27-08-evaluation-metrics-lab-nyc-career-ds-102218
scbronder/dsc-3-29-02-linear-to-logistic-regression-nyc-career-ds-102218
scbronder/dsc-3-29-03-fitting-a-logistic-regression-model-lab-nyc-career-ds-102218
scbronder/dsc-3-29-04-logistic-regression-in-scikit-learn-nyc-career-ds-102218
scbronder/dsc-3-29-06-evaluating-logistic-regression-models-lab-nyc-career-ds-102218
scbronder/dsc-3-29-08-roc-curves-and-auc-nyc-career-ds-102218
scbronder/dsc-3-29-10-class-imbalance-problems-nyc-career-ds-102218
scbronder/dsc-3-31-06-decision-tree-scikitlearn-codealong-nyc-career-ds-102218
scbronder/dsc-3-32-05-gridsearchcv-nyc-career-ds-102218
scbronder/dsc-4-39-02-intro-to-recommendation-systems-nyc-career-ds-102218
scbronder/dsc-4-39-06-building-recommendation-system-als-pyspark-nyc-career-ds-102218
scbronder/sqlalchemy-intro-to-relationships-lab-nyc-career-ds-102218