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