Podcast #31 - AI in Production
This is a conversation with Ashish Patel, Chief Data Scientist at IBM, about Productionalizing AI solutions, best practices and different Cloud Providers. We also touched upon the importance of ML Ops in this whole Machine Learning deployment life cycle.
Spotify link: https://open.spotify.com/episode/1XVc...
Ashish Patel
Ashish Patel is a Chief Data Scientist, AI researcher, and AI Consultant with over 11 years of experience in AI, Currently living in Ahmedabad(INDIA). He has written a book on "Hands-on time series Analysis with Python" with Apress Publication. He has a Master of Engineering Degree from Gujarat Technological University and his keen interest and ambition to research in the following domains such as (Machine Learning, Deep Learning, Time series, Natural Language Processing, Reinforcement Learning, Audio Analytics, Signal Processing, Sensor Technology, IoT, Computer Vision). He is currently working as Chief Data Scientist and Sr.AWS AI ML Solution Architect for IBM. He has published more than 15 + Research papers in the field of Data Science with Reputed Publications such as IEEE. He holds Rank 3 as a kernel master in Kaggle. Ashish has immense experience working on cross-domain projects involving a wide variety of data, platforms, and technologies
Chapters
00:00 Introduction
00:45 Primary hurdles while productionalizing AI solutions
03:46 Things to note while building Production Grade AI solutions
08:30 Common mistakes during the model development and deployment
16:51 Frameworks for scalable AI solutions
26:13 Cloud source provider
28:38 Infrastructure demand
30:20 Algorithm Challenges
33:50 Future