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1. good_wines_bad_wines good_wines_bad_wines Public

   classifying wines with machine learning

   Jupyter Notebook

2. Logistic-Regression Logistic-Regression Public

   The Logic of Logistic Regression: A Tutorial

   HTML 2

3. gradient_boosting_regression gradient_boosting_regression Public

   In this notebook, we'll build from scratch a gradient boosted trees regression model that includes a learning rate hyperparameter, and then use it to fit a noisy nonlinear function.

   HTML

4. Fastai-A-Code-First-Introduction-To-Natural-Language-Processing-TWiML-Study-Group Fastai-A-Code-First-Introduction-To-Natural-Language-Processing-TWiML-Study-Group Public

   For the TWiML NLP Study Group. We review the fast.ai course "A Code-First Introduction to Natural Language Processing", created by Rachel Thomas, of The Data Institute | University of San Francisco…

   Jupyter Notebook 18 10

5. Fastai-Deep-Learning-From-the-Foundations-TWiML-Study-Group Fastai-Deep-Learning-From-the-Foundations-TWiML-Study-Group Public

   Review materials for the TWiML Study Group. Contains annotated versions of the original Jupyter noteboooks (look for names like *_jcat.ipynb ), slide decks from weekly Zoom meetups, etc.

   Jupyter Notebook 26 4

6. seattle-911 seattle-911 Public

   In this mini data science tutorial our task is to predict reasons for 911 calls, given a fictitious 911 calls database. We'll build and test a Random Forest model using Python and scikit-learn.

   Jupyter Notebook 2