A conversation with Aniket Maurya who is a Developer advocate at Lightning AI as well as a Machine Learning Engineer. In the episode we talk about a lot of different things, Lightning, open source machine learning, and touch on topics such as GPT4, developer workflow, and advice for people learning about ML.

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Paid Courses I recommend for learning (affiliate links, no extra cost for you):
⭐ Machine Learning Specialization https://bit.ly/3hjTBBt
⭐ Deep Learning Specialization https://bit.ly/3YcUkoI
📘 MLOps Specialization http://bit.ly/3wibaWy
📘 GAN Specialization https://bit.ly/3FmnZDl
📘 NLP Specialization http://bit.ly/3GXoQuP

✨ Free Resources that are great:
NLP: https://web.stanford.edu/class/cs224n/
CV: http://cs231n.stanford.edu/
Deployment: https://fullstackdeeplearning.com/
FastAI: https://www.fast.ai/

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Timestamps:
0:00 - Introduction
1:00 - Lightning
05:30 - Overview of (Lit) packages
07:40 - Journey to join Lightning team
10:10 - Lightning 2.0
15:00 - GitHub & Slack, and contributing
18:25 - TensorFlow, PyTorch & Jax
23:10 - FastAI and Flash
25:10 - GPT4, AI safety and openness
31:55 - MLOps and Deployment
33:20 - Developer Advocate
36:00 - CoPilot & ChatGPT
40:45 - IDE and programming workflow
44:10 - Next steps for Lightning
49:10 - Learning Machine Learning
52:40 - Advice for beginners
1:01:21 - How important is a degree?
1:05:00 - Following curiosity and interest
1:06:50 - Ending