Deep Learning, Computer Vision & Multimodal • AI Education • MS Engineering AI @ CarnegieMellon
Complete ML Pack: http://nyandwi.com/machine_learning_complete/
The Little Book of Deep Learning, François Fleuret, University of Geneva Arguably one of the most concise deep learning books on the web. Covers a range of topics from fundamentals, efficient computation, training deep models, architectures, applications, and generative tasks.…
Neural Nets for NLP - Carnegie Mellon This is a great course that covers neural networks techniques and algorithms for natural language processing. Covers neural network architectures for language modelling such as recurrent networks and transformers, tips and tricks for…
Prompt Engineering - Article Excellent article on prompt engineering. Covers almost all prompting techniques such as basic prompting strategies(zero-shot, few-shot), instruction prompting, self-consistency, chain of thoughts(CoT), augmented LMs, etc... As opposed to classical…
How to train your own Large Language Models This is a great article on the mechanics of training (your own) large language models. Discusses the importance of training your own LLM, data pipelines, model training, evaluation, and deployment.
