Rank #1: Idea Pandemics and Workshop Walkthrough
Rank #2: Hello World!
Rank #3: Machine Learning and Magical Thinking
Rank #4: Gaussian Processes, Grad School, and Richard Zemel
Rank #5: Jupyter Notebooks and Modern Model Distribution
In episode four of season five we talk about Jupyter Notebooks and Neil's dream of a world craft software and devices, we take a listener question about the conversation surrounding Open AI's GPT-2 its announcement and the coverage and we hear an interview with Brooks Paige of the Alan Turing Instiute
Rank #6: The Bezos Paradox and Machine Learning Languages
Rank #7: Common Sense Problems and Learning about Machine Learning
Rank #8: The Pace of Change and The Public View of ML
In episode ten of season three we talk about the rate of change (prompted by Tim Harford), take a listener question about the power of kernels, and talk with Peter Donnelly in his capacity with the Royal Society's Machine Learning Working Group about the work they've done on the public's views on AI and ML.
Rank #9: Explainability and the Inexplicable
Rank #10: ANGLICAN and Probabilistic Programming
Rank #12: Software and Statistics for Machine Learning
Rank #13: OpenAI and Gaussian Processes
Rank #14: Simulated Learning and Real World Ethics
Rank #15: Getting a Start in ML and Applied AI at Facebook
In episode five of season three we compare and contrast AI and data science, take a listener question about getting started in machine learning, and listen to an interview with Joaquin Quiñonero Candela.
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Rank #16: Generative Art and Hamiltonian Monte Carlo
Rank #18: Good Data Practice Rules
In episode five of season four we talk about the GDPR or as we like to think of it Good Data Practice Rules. (If you actually read it, you move to expert level!) We take a listener question about the power of approximate inference, and we hear from our guest Andrew Blake of The Alan Turing Institute.