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XOP's ( DataOp's, MLOP's) Sig Poc
- 1. #Single Slide - Elevator Pitch, Reproducible Insights, Reference
- 2. Can Manual Feature Engineering can extract better Signals? ( against Auto-ML Feature Engineering) • Research • Identify Explore • Evidence driven • Github Insights • XOP’s Opportunity Pitch
- 3. What Collapsing a categorical value has on a Model? • Research • Identify Explore • Evidence driven • Github Insights • XOP’s Opportunity Pitch
- 5. Can left out sample affect “learnt signal”? Explore • Research • Identify Insights • Evidence driven • Github Pitch • XOP’s Opportunity
- 6. Does Imputation Skew the Learning ? Explore • Research • Identify Insights • Evidence driven • Github Pitch • XOP’s Opportunity
- 7. Is my model the right choice ? Explore Research Identify Insights Evidence driven Github Pitch XOP’s Opportunity
- 8. Can my Validation capture generalization skew ? Explore Research Identify Insights Evidence driven Github Pitch XOP’s Opportunity
- 9. Can I trust my centre? Explore Research Identify Insights Evidence driven Github Pitch XOP’s Opportunity
- 10. Does new data have any new signature? • Research • Identify Explore • Evidence driven • Github Insights • XOP’s Opportunity Pitch
- 11. Did my model learnt any new signature? Explore Research Identify Insights Evidence driven Github Pitch XOP’s Opportuni ty
- 12. Does my optimal Model helps in Scaling? Explore Research Identify Insights Evidence driven Github Pitch XOP’s Opportunity
- 14. For people who like to know .. References Executive Summary https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/an-executives-guide-to-ai https://www.mckinsey.com/featured-insights/artificial-intelligence/notes-from-the-ai-frontier-applications-and-value-of-deep-learning https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/global-survey-the-state-of-ai-in-2020 History https://www.forbes.com/sites/gilpress/2013/05/28/a-very-short-history-of-data-science/#d81ef9555cfc https://www.forbes.com/sites/bernardmarr/2016/02/19/a-short-history-of-machine-learning-every-manager-should-read/#e1bcd315e780 https://www.forbes.com/sites/bernardmarr/2016/03/22/a-short-history-of-deep-learning-everyone-should-read/#7567ed4f5561 https://www.forbes.com/sites/gilpress/2016/12/30/a-very-short-history-of-artificial-intelligence-ai/#3fe830496fba HPE Trainings Beginner Hands-On Deeper Intuition https://www.youtube.com/c/LuisSerrano/playlists https://end-to-end-machine-learning.teachable.com/ https://www.youtube.com/user/joshstarmer Analyst Reports Interesting Blogs https://adeshpande3.github.io/adeshpande3.github.io/The-9-Deep-Learning-Papers-You-Need-To-Know-About.html Recommended Courses Stanford CNN, NLP, Pedigo Dominos ML, Sandford Statistical ML Certification Amazon ML Speciality, Azure DS, G-Cloud ML Books