Super Data Science: ML & AI Podcast with Jon Krohn
En podcast af Jon Krohn
877 Episoder
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316: Make It About Yourself
Udgivet: 22.11.2019 -
315: Making Data Accessible
Udgivet: 21.11.2019 -
314: Meet the Team
Udgivet: 15.11.2019 -
313: The Power of Online Data Education
Udgivet: 14.11.2019 -
312: Contemplation
Udgivet: 8.11.2019 -
311: Using Data Right In Smart Cities
Udgivet: 7.11.2019 -
310: Trial by Fire
Udgivet: 1.11.2019 -
309: Learning Through Competition
Udgivet: 30.10.2019 -
308: Your Tribe
Udgivet: 25.10.2019 -
307: Problem Solving Through Better Thinking
Udgivet: 23.10.2019 -
306: Pura Vida
Udgivet: 18.10.2019 -
305: Using Data Visualization Tools
Udgivet: 16.10.2019 -
304: The Law of Attraction
Udgivet: 11.10.2019 -
303: Proper Hypothesis Testing For Every Field
Udgivet: 9.10.2019 -
302: What is Data Science to you?
Udgivet: 4.10.2019 -
301: Finding Your Edge
Udgivet: 2.10.2019 -
300: Legacy
Udgivet: 27.9.2019 -
299: Becoming Seasoned At Failure
Udgivet: 25.9.2019 -
298: The Six Months Rule
Udgivet: 20.9.2019 -
297: Fortitude & Passion in the Data Science Journey
Udgivet: 18.9.2019
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.