Super Data Science: ML & AI Podcast with Jon Krohn
A podcast by Jon Krohn
877 Episoade
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336: Better Than Perfect
Publicat: 31.01.2020 -
335: Many Ways to Fail & Five Ways to Succeed in Startups
Publicat: 30.01.2020 -
334: No Coaching
Publicat: 24.01.2020 -
333: BERT and NLP in 2020 and Beyond
Publicat: 23.01.2020 -
332: Go through the Motions
Publicat: 17.01.2020 -
331: Hacking Data Science Interviews for Graduates
Publicat: 16.01.2020 -
330: Good!
Publicat: 10.01.2020 -
329: Telling a Story Right with Data
Publicat: 09.01.2020 -
328: Look for the Horse
Publicat: 03.01.2020 -
327: Data Science Trends for 2020
Publicat: 02.01.2020 -
326: Who Inspires You?
Publicat: 27.12.2019 -
325: What I Learned in 2019
Publicat: 26.12.2019 -
324: Proximity is Power #2
Publicat: 20.12.2019 -
323: Data Science as a Freelance Career
Publicat: 19.12.2019 -
322: Diets
Publicat: 13.12.2019 -
321: The Life of One Advanced Data Scientist
Publicat: 12.12.2019 -
320: Mentorship
Publicat: 06.12.2019 -
319: The Path to Data Visualization
Publicat: 05.12.2019 -
318: Amazing
Publicat: 29.11.2019 -
317: A Deep Dive Into Neural Nets
Publicat: 28.11.2019
The latest machine learning, A.I., and data career topics from across both academia and industry are brought to you by host Dr. Jon Krohn on the Super Data Science Podcast. As the quantity of data on our planet doubles every couple of years and with this trend set to continue for decades to come, there's an unprecedented opportunity for you to make a meaningful impact in your lifetime. In conversation with the biggest names in the data science industry, Jon cuts through hype to fuel that professional impact. Whether you're curious about getting started in a data career or you're a deep technical expert, whether you'd like to understand what A.I. is or you'd like to integrate more data-driven processes into your business, we have inspiring guests and lighthearted conversation for you to enjoy. We cover tools, techniques, and implementation tricks across data collection, databases, analytics, predictive modeling, visualization, software engineering, real-world applications, commercialization, and entrepreneurship − everything you need to crush it with data science.
