Someone spent several months manually writing a 200-page guide on mathematics and the basics of machine learning. 📘

No marketing fluff or endless links between articles. Just an attempt to gather all the most important things in one place. 🎯

Inside:

• neural networks: backpropagation, SGD, Adam, BatchNorm; ⚙️
• classic ML: SVM, Gradient Boosting, K-Means, PCA; 📊
• hardware for AI: Tensor Cores, Systolic Arrays, CUDA; 🖥️
• transformers: Multi-Head Attention, KV Cache, LoRA; 🧠
• computer vision: ViT, CNN, MAE, IoU, NMS, VLM; 👁️
• agent systems: ReAct, memory, orchestration, OpenClaw. 🤖

The author describes it as the material he would have wanted to receive himself several years ago. 🕰️

And yes, the entire guide is distributed free of charge. 🆓

https://www.arjunvirk.com/writing/ml-guide

#MachineLearning #AI #DeepLearning #DataScience #NeuralNetworks #Tech

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