Super Data Science: ML & AI Podcast with Jon Krohn
Ein Podcast von Jon Krohn
877 Folgen
-
296: Who You Become
Vom: 13.9.2019 -
295: A Deep Conversation About Tech & Life
Vom: 11.9.2019 -
294: Perception of AI in Big Companies
Vom: 6.9.2019 -
293: True Personalization Through Reinforcement Learning
Vom: 4.9.2019 -
292: Introverts and Extroverts
Vom: 30.8.2019 -
291: Changing the World With Theory & Data
Vom: 28.8.2019 -
290: The Passion Paradox
Vom: 23.8.2019 -
289: AI, Deepfakes and Call of Duty
Vom: 21.8.2019 -
288: Love Yourself
Vom: 16.8.2019 -
287: How To Be Social About Data Science
Vom: 14.8.2019 -
286: Solitude Deprivation
Vom: 9.8.2019 -
285: Bringing Dev & Diverse Communities Into Data Science
Vom: 7.8.2019 -
284: Proximity is Power
Vom: 2.8.2019 -
283: Getting The Most Out of Data With Gradient Boosting
Vom: 31.7.2019 -
282: Learning Something New
Vom: 26.7.2019 -
281: Futureproofing Your Digital Marketing Tactics
Vom: 24.7.2019 -
280: Gap Year
Vom: 19.7.2019 -
279: Embedding Data Science in Business
Vom: 17.7.2019 -
278: Your Core Strength
Vom: 12.7.2019 -
277: The New Age of Reason
Vom: 10.7.2019
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.