Episode 4. The AI Fundamentalists welcome Christoph Molnar to discuss the characteristics of a modeling mindset in a rapidly innovating world. He is the author of multiple data science books including Modeling Mindsets, Interpretable Machine Learning, and his latest book Introduction to Conformal Prediction with Python. We hope you enjoy this enlightening discussion from a model builder's point of view.To keep in touch with Christoph's work, subscribe to his newsletter Mindful Modeler - "Better machine learning by thinking like a statistician. About model interpretation, paying attention to data, and always staying critical."SummaryIntroduction. 0:03Introduction to the AI fundamentalists podcast.Welcome, Christopher MolnarWhat is machine learning? How do you look at it? 1:03AI systems and machine learning systems.Separating machine learning from classical statistical modeling.What’s the best machine learning approach? 3:41Confusion in the space between statistical learning and machine learning.The importance of modeling mindsets.Different approaches to using interpretability in machine learning.Holistic AI in systems engineering.Modeling is the most fun part but also the beginning. 8:19Modeling is the most fun part of machine learning.How to get lost in modeling.How can we use the techniques in interpretable ML to create a system that we can explain to stakeholders that are non-technical? 10:36How to interpret at the non-technical level.Reproducibility is a big part of explainability.Conformal prediction vs. interpretability tools. 12:51Explanability to a data scientist vs. a regulator.Interoperability is not a panacea.Conformal prediction with Python.Roadblocks to conformal prediction being used in the industry.What’s the best technique for a job in data science? 17:20The bandwagon effect of Netflix and machine learning.The mindset difference between data science and other professions.Machine learning is always catching up with the best practices in the industry. 19:21The machine learning industry is catching up with best practices.Synthetic data to fill in gaps.The barrier to entry in machine learning.How to learn from new models.How to train your mindset before you start modeling. 23:52The importance of simplifying two different mindsets.Introduction to conformal prediction with Python.What did you think? Let us know.Do you have a question or a discussion topic for the AI Fundamentalists? Connect with them to comment on your favorite topics: LinkedIn - Episode summaries, shares of cited articles, and more. YouTube - Was it something that we said? Good. Share your favorite quotes. Visit our page - see past episodes and submit your feedback! It continues to inspire future episodes.

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