Live Coding LayerNorm in Pure C | Fixing Tensor Shape & Memory Bugs

In this video, I debug and fix my LayerNorm forward pass implementation while building a Transformer framework entirely in Pure C. This is a full live coding session where I solve tensor issues, memory bugs, and numerical problems step-by-step. If you're interested in: Building Transformers from scratch Low-level ML engineering Autograd systems Memory allocators Tensor infrastructure Pure C machine learning then this series will show the real engineering process behind creating a deep learning framework from scratch. This video focuses on: LayerNorm forward pass implementation Debugging tensor values Fixing shape inconsistencies Memory layout issues Transformer component development 👉 GitHub Repo: https://github.com/umairgillani93/miniTorch 🌐 Connect with me: • GitHub → https://github.com/umairgillani93 #MachineLearning #Transformers #CProgramming #LayerNorm #DeepLearning #Autograd #LLM #SystemsProgramming #PureC #neuralnetworks layer norm, layer normalization, layernorm forward pass, layernorm in c, transformer from scratch, transformer in c, pure c programming, deep learning in c, neural network from scratch, llm from scratch, llm in c, transformer engine, custom autograd, autograd in c, tensor library in c, machine learning systems, systems programming, low level machine learning, memory allocator in c, tensor operations, transformer debugging, debugging neural networks, live coding c programming, c programming tutorial, deep learning implementation, forward pass debugging, transformer architecture, building transformers from scratch, custom transformer framework, neural network engineering, ml engineering, ai systems engineering, memory management in c, tensor engine, layernorm implementation, transformer internals, coding transformers, c language projects, machine learning infrastructure, low level ai engineering