In this episode of the ML mini series, we are introducing Microsoft Team Data Science Process, a process to improve the productivity of the data science organizations of enterprises, and demonstrating an open-source data science utility, named Interactive Data Exploration, Analysis, and Reporting, developed by Microsoft. We are trying to answer the following questions:
- [02:22] What is data science? Why data science is hard?
- [11:13] What is Team Data Science Process (TDSP), why there is a need for TDSP?
- [18:47] What does TDSP offer to improve the productivity of data science organizations?
- [22:05] How does the Interactive Data Exploration, Analysis and Reporting (IDEAR) work? What problems is IDEAR helping address?
- Recent blog post on TDSP: https://blogs.technet.microsoft.com/machinelearning/2017/04/05/latest-rev-of-utilities-for-microsoft-team-data-science-process-tdsp-now-available/
- TDSP GitHub repo: http://aka.ms/tdsp
- TDSP Utilities: http://github.com/Azure/Azure-TDSP-Utilities
- Data Science Project Template repo: http://github.com/Azure/Azure-TDSP-ProjectTemplate
- TDSP Learning Map: http://azure.microsoft.com/en-us/documentation/learning-paths/data-science-process