Super Data Science: ML & AI Podcast with Jon Krohn
A podcast by Jon Krohn
877 Episoade
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476: Peer-Driven Learning
Publicat: 04.06.2021 -
475: The 20% of Analytics Driving 80% of ROI
Publicat: 01.06.2021 -
474: The Machine Learning House
Publicat: 28.05.2021 -
473: Machine Learning at NVIDIA
Publicat: 25.05.2021 -
472: The Learning Never Stops (so Relax)
Publicat: 21.05.2021 -
471: 99 Days to Your First Data Science Job
Publicat: 18.05.2021 -
470: My Favorite Books
Publicat: 14.05.2021 -
469: Learning Deep Learning Together
Publicat: 11.05.2021 -
468: The History of Data
Publicat: 07.05.2021 -
467: High-Impact Data Science Made Easy
Publicat: 04.05.2021 -
466: Good vs. Great Data Scientists
Publicat: 30.04.2021 -
465: Analytics for Commercial and Personal Success
Publicat: 27.04.2021 -
464: A.I. vs Machine Learning vs Deep Learning
Publicat: 23.04.2021 -
463: Time Series Analysis
Publicat: 20.04.2021 -
462: It Could Be Even Better
Publicat: 16.04.2021 -
461: MLOps for Renewable Energy
Publicat: 14.04.2021 -
460: The History of Algebra
Publicat: 09.04.2021 -
459: Tackling Climate Change with ML
Publicat: 07.04.2021 -
458: Behind the Scenes
Publicat: 02.04.2021 -
457: Landing Your Data Science Dream Job
Publicat: 01.04.2021
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.
