Super Data Science: ML & AI Podcast with Jon Krohn
En podcast af Jon Krohn
877 Episoder
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336: Better Than Perfect
Udgivet: 31.1.2020 -
335: Many Ways to Fail & Five Ways to Succeed in Startups
Udgivet: 30.1.2020 -
334: No Coaching
Udgivet: 24.1.2020 -
333: BERT and NLP in 2020 and Beyond
Udgivet: 23.1.2020 -
332: Go through the Motions
Udgivet: 17.1.2020 -
331: Hacking Data Science Interviews for Graduates
Udgivet: 16.1.2020 -
330: Good!
Udgivet: 10.1.2020 -
329: Telling a Story Right with Data
Udgivet: 9.1.2020 -
328: Look for the Horse
Udgivet: 3.1.2020 -
327: Data Science Trends for 2020
Udgivet: 2.1.2020 -
326: Who Inspires You?
Udgivet: 27.12.2019 -
325: What I Learned in 2019
Udgivet: 26.12.2019 -
324: Proximity is Power #2
Udgivet: 20.12.2019 -
323: Data Science as a Freelance Career
Udgivet: 19.12.2019 -
322: Diets
Udgivet: 13.12.2019 -
321: The Life of One Advanced Data Scientist
Udgivet: 12.12.2019 -
320: Mentorship
Udgivet: 6.12.2019 -
319: The Path to Data Visualization
Udgivet: 5.12.2019 -
318: Amazing
Udgivet: 29.11.2019 -
317: A Deep Dive Into Neural Nets
Udgivet: 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.