Evolution to Systems Thinking from Model Thinking
The talk provides a peek into different data science algorithms that come together to power a business like Ola. Area of focus would be on how different models built for different purposes come together to solve one problem and hence it becomes important to view the entire system of these predictive and optimization models and their performance as a whole than improving one model in isolation. Will also be touching upon challenges in measuring and attributing impact of data science algorithms in complex connected systems and strategies for the same.
Outline/Structure of the Experience Report
- Introduction to System Thinking
- Example system of models to solve a business problem at Ola
- Challenges in measurement and attribution of impact
- Summary
Learning Outcome
- Importance of system thinking for data science
- Learnings from Experience building data science products for business
- Handling complexity of connected systems at scale
Target Audience
Data Scientists, Data Engineers, Data Specialists, Machine Learning Engineers, Data Science Enthusiasts
Video
schedule Submitted 4 years ago
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