PagedAttention & KV-Cache Optimization: How vLLM Handles Large Scale Inference
How virtual memory paged block mapping solves GPU memory bottleneck and fragmentation in LLM inference.
Jun 18, 202614 min read59
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#machine-learning
Articles tagged with #machine-learning
Deep Learning Optimizers: Deriving Momentum, RMSProp, and AdamW mathematically
Derive and implement modern deep learning optimizers (SGD, Momentum, RMSProp, and AdamW) from scratch in Python.
Jun 18, 202611 min read10Calculus of Backpropagation: Mathematical Derivation from Scratch with Matrix Derivatives
Derive and implement the backpropagation algorithm from scratch in Python using raw matrix calculus.
Jun 18, 202610 min read22Softmax Function Explained: From Raw Scores to Probabilities
Why every neural network classifier converts its raw output through exponential normalization before calling it a prediction
May 3, 202623 min read224
Dot Product in Machine Learning: The Engine Behind Similarity, Attention, and Neural Networks
From cosine similarity to scaled dot-product attention — how one operation powers modern AI
May 3, 202622 min read588RAG vs Fine-Tuning: When to Use Each (and When to Combine Them)
A practical decision guide with Python code for both paths — choose the right approach before you spend weeks building the wrong one.
Apr 19, 202631 min read51