Adventures in Machine Learning

209 Episodes

1. Where ML and DevOps Meet - ML 108

   Published: 3/17/2023
2. How Does ChatGPT Work? - ML 107

   Published: 3/10/2023
3. Machine Learning for Movie Scripts - ML 106

   Published: 3/3/2023
4. ChatGPT and the Divine - ML 105

   Published: 2/23/2023
5. Deep Learning for Tabular and Time Series Data - ML 104

   Published: 2/16/2023
6. Notebooks vs. IDEs With Fabian Jakobs - ML 103

   Published: 2/9/2023
7. How to think about Optimization - ML 102

   Published: 2/3/2023
8. Protecting Your ML From Phishing And Hackers - ML 101

   Published: 1/27/2023
9. The Disruptive Power of Artificial Intelligence - ML 100

   Published: 1/19/2023
10. A History Of ML And How Low Code Tooling Accelerates Solution Development - ML 099

    Published: 1/6/2023
11. Moving from Dev Notebooks to Production Code - ML 098

    Published: 12/22/2022
12. How to Edit and Contribute to Existing Code Base - ML 097

    Published: 12/15/2022
13. MLflow 2.0 And How Large-Scale Projects Are Managed In The Open Source - ML 096

    Published: 12/1/2022
14. Should you Context Switch when Writing Code? - ML 095

    Published: 11/24/2022
15. How To Recession Proof Your Job - BONUS

    Published: 11/24/2022
16. Important Questions To Ask When Scoping ML Projects - ML 094

    Published: 11/17/2022
17. How To Do Research Spikes - ML 093

    Published: 11/10/2022
18. How to Simplify Data Science with DagsHub Founders - ML 092

    Published: 10/27/2022
19. How to Test ML Code - ML 091

    Published: 10/20/2022
20. AGI, Neuron Simulators, and More with Charles Simon - ML 090

    Published: 10/6/2022