Dr. Jon Krohn

Unofficial, machine-generated summaries, as of 2026-11-09.

↗664: MIT Study: ChatGPT Dramatically Increases Productivity — with Jon Krohn (@JonKrohnLearns)
↗Meta's incredible "CICERO" NLP-negotiation A.I.: real-world applications
↗How Meta's incredible "CICERO" NLP-negotiation A.I. works
↗663: CICERO, the astonishing A.I. negotiator — with Alexander Holden Miller
↗"Online" prediction vs "batch" prediction in machine learning
↗The secrets to engineering great features for machine learning
↗Machine learning isn't magic — but this is why it feels like it
↗662: The Most Popular SuperDataScience Podcast Episodes of 2022 — with Jon Krohn (@JonKrohnLearns)
↗Why you should make your ML application "production-ready"
↗Want to teach at Stanford? Here's how
↗661: Designing Machine Learning Systems — with Chip Huyen
↗Artificial Stupidity: A.I. is really dumb — constraining parameters would help
↗DoubtLab: Why you should doubt your data and fix bad training labels
↗CalmCode: Keep up with the latest open-source data science tools... anxiety-free
↗660: Five Ways to Use ChatGPT for Data Science — with Jon Krohn (@JonKrohnLearns)
↗Prodigy: Annotate Training Data More Efficiently with Scripts
↗spaCy: The Data Scientist's Essential Library for NLP (Natural Language Processing)
↗659: Open-Source Tools for Natural Language Processing — with Vincent Warmerdam
↗What is the future of data engineering?
↗Essential tools for data engineering
↗The right path to becoming a data engineer
↗658: How to Build Data and ML Products Users Love — with Brian T. O'Neill
↗What is data streaming?
↗What data engineering skills should data scientists know?
↗657: How to Learn Data Engineering — with Andreas Kretz (@andreaskayy)
↗All data scientists can benefit from low-code tools
↗What data scientists need to know but don't learn in school
↗How to make data science teams profitable
↗How to make A.I. projects profitable
↗What A.I. transparency is and how it relates to Explainable A.I. (XAI)
↗655: AI ROI: How to get a profitable return on an AI-project investment — with Keith McCormick
↗Robot paints art on a canvas using a genetic algorithm
↗How to turn a product idea into a VC-backed startup
↗How to foster collaboration in a tech startup
↗654: Mike Wimmer: The 14-Year-Old A.I. Entrepreneur
↗Glean’s tech stack: D3, Apache Arrow and DuckDB
↗How is Glean different from other business intelligence tools?
↗653: Efficiently Glean-ing Insights from Vast Data Warehouses — with Carlos Aguilar
↗The top tools for data visualization
↗Using A.I. to create visuals
↗How to effectively use multiple visualizations together
↗652: A.I. Speech for the Speechless — with Jon Krohn (@JonKrohnLearns)
↗The three types of color scales
↗How to select ideal colors for a data visualization
↗651: The Intentional Use of Color in Data Communication — with Kate Strachnyi
↗The Elbow Method
↗The five assumptions of linear regression
↗R-squared and adjusted R-squared metric
↗650: SparseGPT: Remove 100 Billion Parameters but Retain 100% Accuracy — with Jon Krohn
↗Feature scaling
↗Supervised vs. unsupervised machine learning
↗649: Introduction to Machine Learning — with Kirill Eremenko and Hadelin de Ponteves
↗What is the future of data science?
↗Is Data Scientist Still the Sexiest Job of the 21st Century?
↗Which jobs will be replaced by A.I.? (And which jobs will be augmented by A.I.?)
↗648: VALL-E: Uncannily Realistic Voice Imitation from a 3-Second Clip — with Jon Krohn
↗How A.I. can augment human capabilities
↗How can organizations become A.I. fueled?
↗647: Is Data Science Still Sexy? — with Tom Davenport
↗How to file a patent
↗How to transition into data science from a quantitative academic background
↗Using SHAP to explain models
↗646: ChatGPT: How to Extract Commercial Value Today — with Zack Weinberg
↗The future of gaming
↗Tools for real-time machine learning in low-latency gaming
↗645: Machine Learning for Video Games — with Carly Taylor
↗Predictions for the healthcare breakthroughs of the future
↗The future of predicting 4D protein structures
↗Personalized Medicine is slow but A.I. can speed it up
↗644: A Framework for Big Life Decisions — with Myra Strober
↗The use of AI to predict protein structures
↗What is "Biologics A.I."?
↗643: A.I. for Medicine — with Charlotte Deane
↗Better to use an A.I. API or create your own A.I. model?
↗Privacy and AI Trust
↗Data Mesh
↗642: Continuous Calendar for 2023 — with Jon Krohn (@JonKrohnLearns )
↗Multimodal A.I. models
↗Data as a Product
↗641: Data Science Trends for 2023 — with Sadie St. Lawrence
↗Mariya’s favorite software tools
↗What excites Mariya about NLP
↗Mariya’s favorite Python libraries
↗640: What I Learned in 2022 — with Jon Krohn (@JonKrohnLearns)
↗Complex data science topics: How to simplify comprehension
↗The positive social impact of future A.I. applications
↗639: Simplifying Machine Learning — with Mariya Sha (@PythonSimplified)
↗Top tips for presenting data in a slideshow
↗Static vs Interactive Dashboards: When to use which
↗How to report on data effectively
↗638: ChatGPT Holiday Greeting — with @JonKrohnLearns
↗Surprising tricks in Excel
↗Data visualization: best practices
↗637: How to Influence Others with Your Data — with Ann K. Emery (@AnnKEmery)​
↗Spacemacs: Combining the best of Emacs and Vim
↗How Noam Chomsky's language hierarchy ties to computer science
↗Weakly supervised machine learning: What it is and an example application
↗636: The Equality Machine — with Orly Lobel
↗Why you shouldn't manually label data
↗Why bias in machine learning is often good