Super Data Science: ML & AI Podcast with Jon Krohn
Jon Krohn
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.
Episodes
Mentioned books
Nov 4, 2022 • 7min
624: Imagen Video: Incredible Text-to-Video Generation
Investigating Google's Imagen Video, a new text-to-video generator competing against DALL-E 2. This model returns moving images, unlike its predecessor. Jon Krohn explores the technology behind this shiny new tool in the tech giant's arsenal.
11 snips
Nov 1, 2022 • 1h 11min
623: Data Analyst, Data Scientist, and Data Engineer Career Paths
Shashank Kalanithi shares insights on starting a YouTube channel on data science, differences between data roles, applications of data in sports industry, and needs divide between digital native and traditional companies.
Oct 28, 2022 • 24min
622: Burnout: Causes and Solutions
Expert on occupational burnout, Christina Maslach, discusses causes of burnout in the workplace, solutions, and strategies to prevent it. She emphasizes the importance of positive feedback, supportive environments, fair treatment, and ethical alignment. Examples from different professions illustrate ways to address issues like work overload, lack of control, and values conflict to avoid burnout.
Oct 25, 2022 • 1h 12min
621: Blockchains and Cryptocurrencies: Analytics and Data Applications
Chief Economist at Chainalysis, Philip Gradwell, discusses analyzing cryptocurrencies, data analytics pipeline, developing data products, blockchain's impact on technology, and qualities sought in data scientists.
Oct 21, 2022 • 7min
620: OpenAI Whisper: General-Purpose Speech Recognition
In this podcast, Jon Krohn discusses OpenAI's Whisper model, a new tool for improving speech recognition accuracy. The model uses an encoder-decoder transformer trained on a large dataset of labeled speech audio. Find out how to try it for free and explore the development process.
Oct 18, 2022 • 1h 21min
619: Tools for Deploying Data Models into Production
Jon Krohn interviews Erik Bernhardsson, creator of Spotify's music recommendation system. They discuss data science candidate interviews, deploying data models to the cloud, and Erik's approach that turned Spotify into an AI-driven streaming giant. Topics include efficient data teams, interviewing tips, building recommendation systems, working with vectors, using Annoy for search, and tools Erik loves.
Oct 14, 2022 • 4min
618: The Joy of Atelic Activities
Learn about the difference between telic and atelic activities, focusing on finding joy in the experience itself rather than the end goal. Explore how daily actions impact overall fulfillment.
Oct 11, 2022 • 1h 11min
617: Causal Modeling and Sequence Data
Dr. Sean Taylor, Co-Founder of Motif Analytics, discusses causal modeling, large-scale experimentation, Bayesian parameter searches, and the relationship between causality and sequence analytics. He shares insights from his work at Lyft, the importance of causal modeling in decision-making, and tools like Facebook's Prophet for forecasting. Sean also talks about his PhD in Information Systems and what he looks for in data science hires.
Oct 7, 2022 • 6min
616: The Four Requirements for Expertise (beyond the 10,000 Hours)
Explore the four key requirements for expertise development beyond 10,000 hours: valid learning environments, repeated attempts with feedback, timely feedback, and deliberate practice for continuous improvement.
Oct 4, 2022 • 55min
615: How to Ace Your Data Science Interview
Data science expert Jon Krohn speaks with Nick Singh about acing data science interviews, debunking misconceptions, highlighting interview preparation strategies, portfolio essentials, common interview mistakes, shifting mindset for introverts, and great responses to end interviews on the right foot.
