Super Data Science: ML & AI Podcast with Jon Krohn
Podcast autorstwa Jon Krohn
877 Odcinki
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336: Better Than Perfect
Opublikowany: 31.01.2020 -
335: Many Ways to Fail & Five Ways to Succeed in Startups
Opublikowany: 30.01.2020 -
334: No Coaching
Opublikowany: 24.01.2020 -
333: BERT and NLP in 2020 and Beyond
Opublikowany: 23.01.2020 -
332: Go through the Motions
Opublikowany: 17.01.2020 -
331: Hacking Data Science Interviews for Graduates
Opublikowany: 16.01.2020 -
330: Good!
Opublikowany: 10.01.2020 -
329: Telling a Story Right with Data
Opublikowany: 9.01.2020 -
328: Look for the Horse
Opublikowany: 3.01.2020 -
327: Data Science Trends for 2020
Opublikowany: 2.01.2020 -
326: Who Inspires You?
Opublikowany: 27.12.2019 -
325: What I Learned in 2019
Opublikowany: 26.12.2019 -
324: Proximity is Power #2
Opublikowany: 20.12.2019 -
323: Data Science as a Freelance Career
Opublikowany: 19.12.2019 -
322: Diets
Opublikowany: 13.12.2019 -
321: The Life of One Advanced Data Scientist
Opublikowany: 12.12.2019 -
320: Mentorship
Opublikowany: 6.12.2019 -
319: The Path to Data Visualization
Opublikowany: 5.12.2019 -
318: Amazing
Opublikowany: 29.11.2019 -
317: A Deep Dive Into Neural Nets
Opublikowany: 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.
