This podcast overviews some of the challenges associated with implementing AI solutions in a production environment. It offers advice on how to overcome these challenges and discusses the importance of ethical considerations when working with AI technologies.

This video discusses the importance of data versioning, and MLOps, and how to properly use them. It advises data scientists to always follow best practices, use the right tools, and track results.

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