Mar 26 2023 67 mins 11
This episode we welcome Sebastian Raschka, Lead AI Educator at Lightning and author of Machine Learning with Pytorch and Scikit-Learn to discuss the best ways to learn machine learning, his open source work, how to use chatGPT, AGI, responsible AI and so much more. Sebastian is a fountain of knowledge and it was a pleasure to get his insights on this fast moving industry. Learning from Machine Learning, a podcast that explores more than just algorithms and data: Life lessons from the experts. Resources to learn more about Sebastian Raschka and his work:
Machine Learning with Pytorch and Scikit-Learn
Resources to learn more about Learning from Machine Learning and the host: https://www.linkedin.com/company/learning-from-machine-learning
https://www.linkedin.com/in/sethplevine/
https://medium.com/@levine.seth.p
References from Episode
https://scikit-learn.org/stable/
http://rasbt.github.io/mlxtend/
https://github.com/BioPandas/biopandas
Understanding and Coding the Self-Attention Mechanism of Large Language Models From Scratch
Andrew Ng - https://www.andrewng.org/
Andrej Karpathy - https://karpathy.ai/
Paige Bailey - https://github.com/dynamicwebpaige
Contents
01:15 - Career Background
05:18 - Industry vs. Academia
08:18 - First Project in ML
15:04 - Open Source Projects Involvement
20:00 - Machine Learning: Q&AI
24:18 - ChatGPT as Brainstorm Assistant
25:38 - Hype vs. Reality
27:55 - AGI
31:00 - Use Cases for Generative Models
34:01 - Should the goal to be to replicate human intelligence?
39:18 - Delegating Tasks using LLM
42:26 - ML Models are overconfident on Out of Distribution
44:54 - Responsible AI and ML
45:59 - Complexity of ML Systems
47:26 - Trend for ML Practitioners to move to AI Ethics
49:27 - What advice would you give to someone just starting out?
52:20 - Advice that you’ve received that has helped you
54:08 - Andrew Ng Advice
55:20 - Exercise of Implementing Algorithms from Scratch
59:00 - Who else has influenced you?
01:01:18 - Production and Real-World Applications - Don’t reinvent the wheel
01:03:00 - What has a career in ML taught you about life?
