Super Data Science: ML & AI Podcast with Jon Krohn
Podcast autorstwa Jon Krohn
877 Odcinki
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316: Make It About Yourself
Opublikowany: 22.11.2019 -
315: Making Data Accessible
Opublikowany: 21.11.2019 -
314: Meet the Team
Opublikowany: 15.11.2019 -
313: The Power of Online Data Education
Opublikowany: 14.11.2019 -
312: Contemplation
Opublikowany: 8.11.2019 -
311: Using Data Right In Smart Cities
Opublikowany: 7.11.2019 -
310: Trial by Fire
Opublikowany: 1.11.2019 -
309: Learning Through Competition
Opublikowany: 30.10.2019 -
308: Your Tribe
Opublikowany: 25.10.2019 -
307: Problem Solving Through Better Thinking
Opublikowany: 23.10.2019 -
306: Pura Vida
Opublikowany: 18.10.2019 -
305: Using Data Visualization Tools
Opublikowany: 16.10.2019 -
304: The Law of Attraction
Opublikowany: 11.10.2019 -
303: Proper Hypothesis Testing For Every Field
Opublikowany: 9.10.2019 -
302: What is Data Science to you?
Opublikowany: 4.10.2019 -
301: Finding Your Edge
Opublikowany: 2.10.2019 -
300: Legacy
Opublikowany: 27.09.2019 -
299: Becoming Seasoned At Failure
Opublikowany: 25.09.2019 -
298: The Six Months Rule
Opublikowany: 20.09.2019 -
297: Fortitude & Passion in the Data Science Journey
Opublikowany: 18.09.2019
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.
