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
Oct 15, 2021 • 8min
514: Does Caffeine Hurt Productivity? (Part 2: Experimental Results)
Discover the impact of caffeine on productivity through a personal experiment, which shows a substantial increase in deeply focused work without coffee, highlighting the importance of understanding how our habits affect our work performance.
Oct 12, 2021 • 54min
513: Transformers for Natural Language Processing
Denis Rothman, author of books on NLP and explainable AI, discusses transformers' applications, his book on explainable AI, AI by Example, and answers LinkedIn audience questions. Topics include ethical data handling, trillion-parameter transformer models, and exploring transformer architectures like GPT-3 and BERT for NLP tasks.
Oct 8, 2021 • 6min
512: Does Caffeine Hurt Productivity? (Part 1)
Exploring the impact of caffeine on productivity, the host shares personal reflections and anecdotes on whether caffeine is hurting productivity. The episode delves into the decision to conduct an experiment comparing productivity on days witth coffee versus without.
Oct 5, 2021 • 1h 9min
511: Data Science for Private Investing — LIVE with Drew Conway
Drew Conway, an expert in data science for private investing, discusses his work at Two Sigma. Topics include the R Conference, machine learning for hackers, team structure at Two Sigma, and audience Q&A. The episode delves into the evolution of the R Conference, the value of community involvement for data science professionals, the Venn diagram in data science, and the future of data science as an interdisciplinary discipline.
Oct 1, 2021 • 7min
510: Deep Reinforcement Learning
Explore the basics of reinforcement learning and how algorithms interact with environments to maximize rewards. Discover the integration of neural networks with reinforcement learning to make optimal decisions in complex environments.
Sep 28, 2021 • 1h 21min
509: Accelerating Start-up Growth with A.I. Specialists
Parinaz Sobhani discusses Georgian's work in helping startups with AI, emphasizing tools and approaches, environmental concerns, hiring criteria, her career interest in AI, fairness in AI, and the importance of communication and full-stack proficiency for data scientists and ML engineers.
Sep 24, 2021 • 3min
508: Building Your Ant Hill
The podcast discusses the cyclical nature of life and draws parallels to ants rebuilding their anthills. It highlights finding happiness in building relationships and pursuing passions.
Sep 21, 2021 • 1h 55min
507: Bayesian Statistics
Rob Trangucci, an expert in Bayesian statistics, discusses applying it to real-world problems, the Stan package, multi-modal deep learning, the day-to-day of a PhD in stats, and the future of Bayesian stats.
Sep 17, 2021 • 9min
506: Supervised vs Unsupervised Learning
Exploring the differences between supervised and unsupervised learning in machine learning. Learn how supervised learning uses labeled data to predict output labels, while unsupervised learning discovers patterns in unlabeled data. Examples like word embeddings and generative adversarial networks illustrate the distinctions between these two learning approaches.
Sep 14, 2021 • 46min
505: From Data Science to Cinema
Data science educator turned actor Hadelin de Ponteves discusses his transition to a cinema career, the importance of sleep for productivity, decision-making processes, and the contrasts between Bollywood and Hollywood industries.
