Super Data Science: ML & AI Podcast with Jon Krohn
En podcast af Jon Krohn
877 Episoder
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476: Peer-Driven Learning
Udgivet: 4.6.2021 -
475: The 20% of Analytics Driving 80% of ROI
Udgivet: 1.6.2021 -
474: The Machine Learning House
Udgivet: 28.5.2021 -
473: Machine Learning at NVIDIA
Udgivet: 25.5.2021 -
472: The Learning Never Stops (so Relax)
Udgivet: 21.5.2021 -
471: 99 Days to Your First Data Science Job
Udgivet: 18.5.2021 -
470: My Favorite Books
Udgivet: 14.5.2021 -
469: Learning Deep Learning Together
Udgivet: 11.5.2021 -
468: The History of Data
Udgivet: 7.5.2021 -
467: High-Impact Data Science Made Easy
Udgivet: 4.5.2021 -
466: Good vs. Great Data Scientists
Udgivet: 30.4.2021 -
465: Analytics for Commercial and Personal Success
Udgivet: 27.4.2021 -
464: A.I. vs Machine Learning vs Deep Learning
Udgivet: 23.4.2021 -
463: Time Series Analysis
Udgivet: 20.4.2021 -
462: It Could Be Even Better
Udgivet: 16.4.2021 -
461: MLOps for Renewable Energy
Udgivet: 14.4.2021 -
460: The History of Algebra
Udgivet: 9.4.2021 -
459: Tackling Climate Change with ML
Udgivet: 7.4.2021 -
458: Behind the Scenes
Udgivet: 2.4.2021 -
457: Landing Your Data Science Dream Job
Udgivet: 1.4.2021
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.
