Super Data Science Jon Krohn and Guests on Machine Learning, A.I., and Data-Career Success

Hollywood has officially fallen for the drama of tech startups! Tune in to hear Jon Krohn review the small-screen adaptations of WeWork (WeCrashed), Uber (Super Pumped), and Theranos (The Dropout).

Additional materials: www.superdatascience.com/576

In this episode, the Director of Architecture at NVIDIA, Dr. Magnus Ekman, joins Jon Krohn to discuss how machine learning, including deep learning, can optimize computer hardware design. The pair also review his exceptional book 'Learning Deep Learning.'

In this episode you will learn:
• What hardware architects do [10:15]
• How ML can optimize hardware speed [ 13:19]
• Magnus’s Deep Learning Book [21:14]
• Is understanding how ML models work important? [36:16]
• Algorithms inspired by biological evolution [41:25]
• How artificial general intelligence won’t be obtained by increasing model parameters alone [51:24]
• Why there will always be a place for CNNs and RNNs [54:51]
• How people can "transition" realistically into ML [1:09:15]

Additional materials: www.superdatascience.com/575

In this episode, Jon shares how the right music can power your productivity. It's no secret that he's a big fan of 'deep work,' but this week, he opens up about the artists, sites, and playlists that propel his productivity to new levels.

Additional materials: www.superdatascience.com/574

In this episode, co-founder and CEO of Linea, Dr. Doris Xin, joins Jon Krohn to discuss how automating ML model deployment delivers groundbreaking change to data science productivity, and shares what it's like being the CEO of an exciting, early-stage tech start-up.

In this episode you will learn:
• How Linea reduces ML model deployment down to a couple of lines of Python code [5:14]
• Linea use cases [11:30]
• How DAGs can 10x production workflow efficiency [22:12]
• ML model graphlets and reducing wasted computation [24:14]
• What future Doris envisions for autoML [35:23]
• Doris’s day-to-day life as a CEO of an early-stage start-up [42:43]
• What Doris looks for in the engineers and data scientists that she hires [52:21]
• The future of Data Science and how to prepare best for it [53:58]

Additional materials: www.superdatascience.com/573

In this episode, Jon shares his habit of blocking out two hours in his mornings that are free from email and social media distractions. Tune in to learn how this habit helps him deeply focus on his most delightful tasks of the day.

Additional materials: www.superdatascience.com/572

Einblick co-founder and associate professor at MIT, Tim Kraska, joins Jon Krohn to discuss no-code collaboration tools for data science and uncovers the clever database and machine learning tricks under the hood of the visual data computing platform.

In this episode you will learn:
• The inspiration behind Einblick [2:45]
• Einblick's progressive approximation engine [6:43]
• How no-code tools impact productivity [17:18]
• The critical steps to become more data-driven as an organization [24:30]
• How research universities like MIT support high-risk, long-term research [38:37]
• How ML applied to databases enables them to be faster and more efficient [42:03]
• How real-time collaboration environments like Google Docs are likely to become more widespread for data science tasks [ 49:24]

Additional materials: www.superdatascience.com/571