Sandy1811/ml-workflow-sklearn-pipeline

How to Simplify Machine Learning Workflow with scikit-learn Pipeline

This notebook is apart of Ageas - Knowledge Hub Webinar - 7/May/2019

Requirements

Python 3.X

Authors

• Siraprapa Watakit

License

This project is licensed under the MIT License - see the LICENSE.md file for details

Credits

• Zac Stewart
• Julie Michelman
• Kevin Goetsch
• Kevin Markham

Also very good to check all these out :-

1. Kevin Markham - Machine Learning Series / Pandas Best Practices:

• https://www.youtube.com/watch?v=elojMnjn4kk&list=PL5-da3qGB5ICeMbQuqbbCOQWcS6OYBr5A – This series also covers GridSearch
• https://www.youtube.com/playlist?list=PL5-da3qGB5IBITZj_dYSFqnd_15JgqwA6

2. Julie Michelman/Kevin Goetsch on sklearn Pipeline – I derived lots from their training

• https://www.youtube.com/watch?v=BFaadIqWlAg
• https://www.youtube.com/watch?v=URdnFlZnlaE

3. Zac Stewart blogs – of which he explains how he put 10 machine leaning in1 pipeline

• http://zacstewart.com/2014/08/05/pipelines-of-featureunions-of-pipelines.html

4. This is my silly NLP ,of which I compare multiple models metrics – NLP/Sentiment /w and wo Pipeline, go to the bottom

• https://nbviewer.jupyter.org/github/swatakit/The-public-and-private-life-of-Big-Data/blob/master/StockSentimentIndex.ipynb

5. I talked about RIDITS, which one of many unsupervised learning methods for Fraud detection, there are many more ways of to do so – I highly recommend this

• Elena Sharova / Fraud detection in banking - https://www.youtube.com/watch?v=5p8B2Ikcw-k
• Brian Kent https://www.youtube.com/watch?v=5cOhL4B5waU

6. Python Data Science Handbook

• https://jakevdp.github.io/PythonDataScienceHandbook/

7. Finally, RISE and how to use it?

• https://www.youtube.com/watch?v=utNl9f3gqYQ