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