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Coding for ML

NumPy, PyTorch, and the round where you implement it from scratch.

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๐ŸŸกImplement Linear Regression from Scratchmust-know5 min๐Ÿ”ดImplement Self-Attention from Scratchmust-know5 min๐ŸŸขNumPy Broadcasting & Vectorization5 min๐ŸŸขPandas: GroupBy, Merge, Window5 min๐ŸŸกImplement Logistic Regression from Scratch5 min๐ŸŸกImplement k-Means from Scratch5 min๐ŸŸกImplement k-NN Efficiently5 min๐ŸŸกImplement Softmax + Cross-Entropy Stably5 min๐ŸŸกImplement Vector Similarity Search5 min๐ŸŸกImplement ROC-AUC from Scratch5 min๐ŸŸกImplement Non-Max Suppression5 min๐ŸŸกViews, Copies & Memory in NumPy5 min๐ŸŸกThe PyTorch Training Loop5 min๐ŸŸกDataset & DataLoader Patterns5 min๐ŸŸกMaking Pandas Fast5 min๐ŸŸกComplexity Questions in ML Coding5 min๐ŸŸกYour Loss Is NaN. Now What?5 min๐ŸŸกWriting ML Code Someone Else Can Run5 min๐Ÿ”ดImplement Multi-Head Attention5 min๐Ÿ”ดImplement Backprop for an MLP5 min๐Ÿ”ดImplement BatchNorm Forward & Backward5 min๐Ÿ”ดImplement Conv2D from Scratch5 min๐Ÿ”ดImplement a Decision Tree Split5 min๐Ÿ”ดImplement a Toy BPE Tokenizer5 min๐Ÿ”ดAutograd Gotchas: detach, no_grad, retain_graph5 min