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Tutorial updates after feedback
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tutorials/ensembles-stacking/README.md

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> # !!! UNDER CONSTRUCTION !!!
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> (But open the book anyway, we're adding content...)
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# Ensembles: Stacking, Super Learner, Subsemble
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- Overview
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- What is Ensemble Learning?

tutorials/intro-to-datascience/README.md

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# Introduction to Data Science, Machine Learning & Predictive Analytics
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- Overview
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- What is Data Science?
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- Data Science Tasks
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- Problem Formulation
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- Problem Formulation (motivation)
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- Collect & Process Data
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- Machine Learning
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- Insights & Action
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- Training Data:
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- Features:
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- Models:
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- Model Validation:
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- Overfitting: ?
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- Supervised Learning:
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- Unsupervised Learning:
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![DS Google Trends](images/ml_workflow.png)
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Data scientist built a black-box model. Need a cluster to productionize model. Network pipeline bringing data in (IT and Hardware involved)
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TO DO: Add a slide about how this fits into the IT pipeline and business.
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## References
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[1] [https://www.reddit.com/r/MachineLearning/comments/2fxi6v/ama_michael_i_jordan/ckelmtt](https://www.reddit.com/r/MachineLearning/comments/2fxi6v/ama_michael_i_jordan/ckelmtt)
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# Topics in Model Selection
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- Overview
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- Performance Metrics
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- Supervised
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- Regression
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- Binomial Classification
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- Multinomial Classification
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- Ranking
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- Unsupervised
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- Train & Test
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TO DO: Code example
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- Cross-validation
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- Grid Search
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- Performance Metrics
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TO DO: Code example
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- Hyperparameter Search
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TO DO: Code example
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- Grid (cartesian)
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- Random
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- etc
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- Model interpretability
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TO DO: Code example
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## Overview
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## Performance Metrics
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## Train & Test
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## Cross-validation
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## Grid Search
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## Performance Metrics
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## Hyperparameter Search
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