Dr. Jon Krohn

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

↗The Most Important Component in Building the Best Product
↗SDS 578: Identifying Commercial ML Problems — with Jon Krohn
↗The Easy and Hard Parts of Scaling an AI Company like Onfido
↗Disrupting the 150-year-old Credit-Footprint Industry with Data Science
↗SDS 577: Scaling A.I. Startups Globally
↗The Importance of Ethical AI
↗Using RNNs instead of Transformers for NLP
↗What is Evolutionary Computation?
↗SDS 576: Tech Startup Dramas — with Jon Krohn
↗How Machine Learning Works: Do you need to know?
↗Machine Learning for Hardware Architecture
↗SDS 575: Optimizing Computer Hardware with Deep Learning — with Magnus Ekman
↗The Biggest A.I. Opportunities of the Future
↗Will AutoML Replace Data Scientists?
↗SDS 574: Music for Deep Work — with Jon Krohn
↗What are DAGs and how can they speed up ML model development?
↗How to Deploy Machine Learning Models into Production Easily
↗SDS 573: Automating ML Model Deployment — with Doris Xin
↗Instance-Optimized Systems and Learned Bloom Filters
↗Three Steps to a Data-Driven Company
↗Will No-Code Data Science Become Mainstream?
↗SDS 572: Daily Habit #9: Avoiding Messages Until a Set Time Each Day — with Jon Krohn
↗How No-Code Environments can Improve Data Team Productivity
↗What is a Progressive Approximation Engine?
↗SDS 571: Collaborative, No-Code Machine Learning — with Tim Kraska
↗How to Become an A.I. Researcher
↗Why do A.I. Research at a Big Tech Company instead of at a University?
↗SDS 570: DALL-E 2: Stunning Photorealism from Any Text Prompt — with Jon Krohn
↗Real-world Applications of Game-Playing A.I. Research
↗Computational Game Theory Strengthens Game-Playing A.I.
↗SDS 569: A.I. For Crushing Humans at Poker and Board Games — with Noam Brown
↗Credit where due: a taxonomy for author metadata
↗The best open-source model
↗How to make STEM more welcome to everyone
↗SDS 568: PaLM: Google's Breakthrough Natural Language Model — with Jon Krohn
↗Addressing STEM biases through publishing
↗The value of open access for anyone doing research and development
↗SDS 567: Open-Access Publishing — with Amy Brand
↗How to become an AI Safety Expert
↗The Theoretical Benefits of AGI
↗The Existential Risks of AGI and ASI
↗SDS 566: The Best Time to Plant a Tree — with Jon Krohn
↗The Difference Between AI and AGI
↗The difference between the Canadian and the US start-up ecosystems
↗SDS 565: AGI: The Apocalypse Machine — with Jeremie Harris
↗Data science when you don’t have enough data
↗Software languages data scientist @TinaHuang1 uses day-to-day
↗How a science background is helpful for data science
↗How a computer science background is helpful for data science
↗SDS 564: Clem Delangue on Hugging Face and Transformers
↗How to start in Data Science from scratch with @TinaHuang1
↗SDS 563: How to Rock at Data Science — with @TinaHuang1
↗How scientists and engineers can make a big social impact in health technology
↗What start-up CTO Nate Fox looks for when hiring
↗How to ensure uptime and reliability of APIs
↗SDS 562: Daily Habit #8: Math or Computer Science Exercise — with Jon Krohn
↗Designing a data API from scratch
↗What is an API?
↗SDS 561: Engineering Data APIs — with Nate Fox
↗Using AI to tackle climate change
↗Accessing GPT-3 via the OpenAI API
↗Mitigating data set bias in natural language models
↗SDS 560: Daily Habit #7: Read Two Pages — with Jon Krohn
↗Fine-tuning GPT-3
↗What is autoregression?
↗SDS 559: GPT-3 for Natural Language Processing — with Melanie Subbiah
↗Top Software Libraries for Working with Tabular Data with Matt Harrison
↗How many rows and columns can a pandas DataFrame load?
↗How to Master Pandas with Matt Harrison
↗SDS 558: @JonKrohnLearns's Answers to Questions on Machine Learning
↗Why Data Scientists should know Git and the Unix command line
↗Top Five Tricks for Coding in Pandas — with Matt Harrison
↗SDS 557: Effective Pandas — with Matt Harrison
↗What Sport Has The Most Sports Analytics Potential according to @KenJee_ds
↗@KenJee_ds's #66DaysofData
↗The Value of @KenJee_ds's Domain Knowledge in His Data Science Work
↗SDS 556: @JonKrohnLearns's Machine Learning Courses
↗How @KenJee_ds Got Started with YouTube
↗@KenJee_ds on How to Get Started in Data Science Today
↗SDS 555: Sports Analytics and 66 Days of Data with @KenJee_ds
↗Essential Statistics Concepts Businesspeople Need to Know according to ​@statquest
↗@statquest Inspiring Story: Leaving Josh's Academic Career
↗Using Grid.ai to Train Cloud ML Models from your Laptop — with @statquest
↗SDS 554: @JonKrohnLearns's Deep Learning Courses
↗How @statquest Got its Name
↗The Inspiration Behind the @statquest Channel
↗SDS 553: The Stats and Machine Learning Quests of Josh Starmer from @statquest
↗SDS 552: The Most Popular SuperDataScience Episodes of 2021 — with Jon Krohn
↗SDS 551: Deep Reinforcement Learning — with Wah Loon Keng
↗SDS 550: Daily Habit #6: Write Morning Pages — with Jon Krohn
↗SDS 549: Engineering Natural Language Models — with Lauren Zhu
↗SDS 548: Daily Habit #5: Meditate — with Jon Krohn
↗SDS 547: How Genes Influence Behavior — with Prof. Jonathan Flint
↗SDS 546: Daily Habit #4: Alternate-Nostril Breathing — with Jon Krohn
↗SDS 545: Scaling Data-Intensive Real-Time Applications — with Matthew Russell
↗SDS 544: Daily Habit #3: Make Your Bed — with Jon Krohn
↗SDS 543: Sparking A.I. Innovation — with Nicole Büttner
↗SDS 542: Continuous Calendar for 2022 — with Jon Krohn
↗SDS 541: Data Observability — with Dr. Kevin Hu
↗SDS 540: Daily Habit #2: Start the Day with a Glass of Water — with Jon Krohn