Datacast Episode 2: Becoming a Deep Learning Expert with Deep Narain Singh

I’m creating a new podcast about Data Science called Datacast! The 2nd episode is my interview with Deep Narain Singh, Deep Learning Engineer at NVIDIA AI. Listen to learn more about his journey moving from India to the US, computer vision and NLP projects he built during graduate school, advice for those who want to get into deep learning, and many more.

Guest Bio

Deep Narain Singh is Data Scientist with specialization in machine learning and deep learning. He has extensive work experience in building NLP/Computer Vision products using AI/ML/DL. He has spent 12 years in industry working with startups and large scale companies. He holds a Master’s degree in Data Science from the University Of New Haven/Galvanize and completed his undergraduate in Civil Engineering from NIT Jaipur.


Show Notes

  • (1:58) Deep gives a brief background on his career.

  • (3:42) Deep explains the discipline of civil engineering.

  • (4:24) Deep talks about his first job out of college as a programmer analyst at Cognizant in Pune, India.

  • (5:26) Deep then became a senior software engineer at the investment bank Citigroup in Mumbai, India.

  • (7:30) Deep discusses his next role as a senior associate for the e-commerce company Sapient in Bangalore, India.

  • (8:57) Deep then went to Barclays Investment Bank back in Pune and worked as an analyst, in which he learned a lot about big data technologies.

  • (10:07) Deep talks about the diverse Indian cultures as he had experience working in many different regions in India.

  • (12:22) Deep recounts the story that propelled him to explore study opportunities in the United States.

  • (16:10) Deep gives practical advice to international students who want to pursue a graduate degree in the US.

  • (17:53) Deep talks about the Machine Learning and Deep Learning classes he took while at Galvanize.

  • (19:27) As a graduate student researcher, Deep built an image captioning system for a startup named FoxType, which helps non-native English speaker write better emails. He goes over the challenges of building this system.

  • (24:55) As a deep learning research intern for, Deep built a system with memory using a neural network to solve the shortcoming of understanding long-term conversation and context for a conversational agent. He discusses the process he went through.

  • (27:59) Deep talks about his machine learning project in which he built a sentiment analysis engine using the 300k reviews from Trip Advisor.

  • (31:33) Deep talks about another data engineering project in which he built an end-to-end real-time mapping of geo-location in San Francisco for Uber Price Surge.

  • (37:32) Deep recommend the big data tools and technologies that all data scientists should know about.

  • (39:27) Deep shares his job search experience and how he landed a role at Nvidia.

  • (42:02) Deep provides helpful advice to crack the machine learning interview (aka, learning the fundamentals + networking).

  • (45:14) Deep talks about the autonomous vehicle system he’s working on at Nvidia.

  • (47:20) Deep quickly goes over Nvidia’s company culture.

  • (49:32) Deep digs deep into computer vision problems.

  • (51:34) Deep predicts the future applications of deep learning.

  • (53:40) Closing segments.

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