Super Data Science: ML & AI Podcast with Jon Krohn
Un pódcast de Jon Krohn
877 Episodo
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316: Make It About Yourself
Publicado: 22/11/2019 -
315: Making Data Accessible
Publicado: 21/11/2019 -
314: Meet the Team
Publicado: 15/11/2019 -
313: The Power of Online Data Education
Publicado: 14/11/2019 -
312: Contemplation
Publicado: 8/11/2019 -
311: Using Data Right In Smart Cities
Publicado: 7/11/2019 -
310: Trial by Fire
Publicado: 1/11/2019 -
309: Learning Through Competition
Publicado: 30/10/2019 -
308: Your Tribe
Publicado: 25/10/2019 -
307: Problem Solving Through Better Thinking
Publicado: 23/10/2019 -
306: Pura Vida
Publicado: 18/10/2019 -
305: Using Data Visualization Tools
Publicado: 16/10/2019 -
304: The Law of Attraction
Publicado: 11/10/2019 -
303: Proper Hypothesis Testing For Every Field
Publicado: 9/10/2019 -
302: What is Data Science to you?
Publicado: 4/10/2019 -
301: Finding Your Edge
Publicado: 2/10/2019 -
300: Legacy
Publicado: 27/9/2019 -
299: Becoming Seasoned At Failure
Publicado: 25/9/2019 -
298: The Six Months Rule
Publicado: 20/9/2019 -
297: Fortitude & Passion in the Data Science Journey
Publicado: 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.