Resources

Tutorials / Courses / Repos / Relevant papers

• ML Tutorials: https://machinelearningmastery.com/
  
• AI Python for beginners (free online course): https://www.deeplearning.ai/short-courses/ai-python-for-beginners/
  
• LLM Interpretability: https://www.neelnanda.io/mechanistic-interpretability/favourite-papers
  
• FDA guidelines: https://www.fda.gov/medical-devices/software-medical-device-samd/good-machine-learning-practice-medical-device-development-guiding-principles
  
• Transformers in Time Series: https://github.com/qingsongedu/time-series-transformers-review
• ChatGPT Leak: https://the-decoder.com/gpt-4-architecture-datasets-costs-and-more-leaked/

Books

• Machine Learning with Python Cookbook: https://www.oreilly.com/library/view/machine-learning-with/9781491989371/
• Deep Learning mit Python und Keras: https://www.amazon.de/-/en/Francois-Chollet/dp/3958458386
• Deep Learning by Ian Goodfellow: https://www.deeplearningbook.org/
• Probabilistic Machine Learning by Murphy: https://probml.github.io/pml-book/book1.html

People

• AI founder and influencer: https://www.ykilcher.com/
• Youtuber: https://www.youtube.com/@NicholasRenotte

Relevant papers

• Transformers: https://arxiv.org/abs/1706.03762
• KAN Networks: https://arxiv.org/abs/2404.19756
  

AI Association resources and past talks

• Machine Learning in Data-Driven marketing: https://github.com/AndreasKarasenko/presentation_10-2024