Super Data Science: ML & AI Podcast with Jon Krohn
Ein Podcast von Jon Krohn
877 Folgen
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096: Bayes Theorem
Vom: 13.10.2017 -
095: From Uber to Data Science – A Winner’s Journey
Vom: 11.10.2017 -
094: The Power of Now
Vom: 6.10.2017 -
093: Why Evolutionary Programming Machine Learning is Important
Vom: 4.10.2017 -
092: Exponential Thinking
Vom: 29.9.2017 -
091: Lessons From a Successful Career in Data Visualization
Vom: 27.9.2017 -
090: Do What You Want
Vom: 22.9.2017 -
089: Using Excel in Data Science and Life-Long Learning
Vom: 20.9.2017 -
088: Fermi Questions
Vom: 15.9.2017 -
087: Business Intelligence – The Role of Data Visualization
Vom: 13.9.2017 -
086: Computer Vision
Vom: 8.9.2017 -
085: The AI Revolution – What the Future Will Look Like
Vom: 6.9.2017 -
084: Why I Became Vegetarian
Vom: 1.9.2017 -
083: Leveraging Your Experience into Data Science
Vom: 30.8.2017 -
082: Data Science Go
Vom: 25.8.2017 -
081: Data Visualization & How to Freelance Your Passion
Vom: 23.8.2017 -
080: Your Questions
Vom: 19.8.2017 -
079: Reinforcement Learning - What You Need to Know
Vom: 16.8.2017 -
078: Breaking Patterns
Vom: 11.8.2017 -
077: Finding the Right Data Science Company That Best Fits You
Vom: 9.8.2017
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.
