Today, many companies want to build applications that use Machine Learning (ML). There is a darth of resources on best practices for managing machine learning projects and methods for understanding, managing, and mitigating the risks some organizations might face in the delivery of these complex systems.
Learn how to manage machine learning projects from the concept stage to the final completion stage. Kiran R draws on his rich experience in the machine learning field to explain various aspects of a typical ML project, including how to successfully manage one from scratch.
Key Takeaways:
- Converting a Business Problem to a Data Mining Problem
- Feature Engineering Strategy
- Modelling Success Tips & Last Mile Optimization
- Getting the ML System implemented
Check out the video below to know more about the talk.
