✳flâneur — a map of the web's best reading

Neural Networks: Zero To Hero

karpathy.ai · 805 words · saved by 6 readers

Neural Networks: Zero to Hero A course by Andrej Karpathy on building neural networks, from scratch, in code. We start with the basics of backpropagation and build up to modern deep neural networks, like GPT. In my opinion language models are an excellent place to learn deep learning, even if your intention is to eventually go to other areas like computer vision because most of what you learn will be immediately transferable. This is why we dive into and focus on languade models. Prerequisites: solid programming (Python), intro-level math (e.g. derivative, gaussian). Learning is easier with others, come say hi in our Discord channel: Syllabus 2h25m The spelled-out intro to neural networks and backpropagation: building micrograd This is the most step-by-step spelled-out explanation of backpropagation and training of neural networks. It only assumes basic knowledge of Python and a vague recollection of calculus from high school. 1h57m The spelled-out intro to language modeling: buildin

Neural Networks: Zero To Hero Neural Networks: Zero to Hero A course by Andrej Karpathy on building neural networks, from scratch, in code. We start with the basics of backpropagation and build up to modern deep neural networks, like GPT. In my opinion language models are an excellent place to learn deep learning, even if your intention is to eventually go to other areas like computer vision because most of what you learn will be immediately transferable. This is why we dive into and focus on languade models. Prerequisites: solid programming (Python), intro-level math (e.g. derivative, gaussia

Explore this link on the map →

saved by

related reading