Machine Learning Resources

Useful guides I’ve been working with

It’s been a while again! ;)

Recently, I’ve been playing a lot with Machine Learning and trying to teach myself the ropes.

People:

• https://twitter.com/ch402

• http://colah.github.io

• https://twitter.com/karpathy
• https://github.com/Vision-CAIR/MiniGPT-4
• https://www.youtube.com/watch?v=kCc8FmEb1nY
• https://colab.research.google.com/drive/1JMLa53HDuA-i7ZBmqV7ZnA3c_fvtXnx-

Tutorial:

• https://www.kaggle.com/learn/intro-to-machine-learning

Papers:

• https://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf - 2012 paper by Alex Krizhevsky in collaboration with Ilya Sutskever and Geoffrey Hinton (https://en.wikipedia.org/wiki/AlexNet)
• https://arxiv.org/abs/1706.03762 - Attention Is All You Need (introduces transformers)
• https://arxiv.org/abs/2304.03442 - Generative Agents: Interactive Simulacra of Human Behavior

Books:

• https://www.amazon.com/Genius-Makers-Mavericks-Brought-Facebook/dp/1524742678
• https://www.amazon.com/Superintelligence-Nick-Bostrom-audiobook/dp/0199678111

Services/infrastucture:

• wandb
• huggingface
• huggingface spaces
• gradio