Mihail Eric is the founder of Pametan Data Innovation, a machine learning consultancy focused on helping organizations build data-driven systems to solve their toughest business problems. He's also the founder of Confetti AI, the premier educational platform for practitioners learning the skills to succeed in their machine learning and data science careers. His career has spanned machine learning industry, research, and engineering across domains such as conversational AI and self-driving vehicles. He has published papers at some of the world's top conferences including ACL, AAAI, and NeurIPS. He has helped start teams at innovative companies like RideOS and Amazon Alexa. Systems that he has architected are used by hundreds of thousands of people globally. He actively blogs and speaks about machine learning. And can be reached on Twitter and LinkedIn.
In this episode, we cover a range of topics including:
Mihail's journey into the world of machine learning:
- How he entered the world of machine learning
- His learnings from running a machine learning consultancy firm
- The role of educational platform and his learnings from building Confetti AI
Careers, Jobs, and Interviews:
- How do you guide new professionals in evaluating what area they like within ML?
- How should a machine learning professional look for jobs?
- How do you interview people?
- What are some of the red flags during hiring?
Product:
- How should ML professionals talk to users/customers?
- How important is the ability to write production-level code?
Overall trends:
- What product that you've personally used has impressed you the most? And why?
- What has been the biggest positive development in ML compared to 5 years ago?
- Looking forward, what aspect of ML excites you the most?
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By Prateek Joshi
4.9
88 ratings
Mihail Eric is the founder of Pametan Data Innovation, a machine learning consultancy focused on helping organizations build data-driven systems to solve their toughest business problems. He's also the founder of Confetti AI, the premier educational platform for practitioners learning the skills to succeed in their machine learning and data science careers. His career has spanned machine learning industry, research, and engineering across domains such as conversational AI and self-driving vehicles. He has published papers at some of the world's top conferences including ACL, AAAI, and NeurIPS. He has helped start teams at innovative companies like RideOS and Amazon Alexa. Systems that he has architected are used by hundreds of thousands of people globally. He actively blogs and speaks about machine learning. And can be reached on Twitter and LinkedIn.
In this episode, we cover a range of topics including:
Mihail's journey into the world of machine learning:
- How he entered the world of machine learning
- His learnings from running a machine learning consultancy firm
- The role of educational platform and his learnings from building Confetti AI
Careers, Jobs, and Interviews:
- How do you guide new professionals in evaluating what area they like within ML?
- How should a machine learning professional look for jobs?
- How do you interview people?
- What are some of the red flags during hiring?
Product:
- How should ML professionals talk to users/customers?
- How important is the ability to write production-level code?
Overall trends:
- What product that you've personally used has impressed you the most? And why?
- What has been the biggest positive development in ML compared to 5 years ago?
- Looking forward, what aspect of ML excites you the most?
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