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