Learn how neural networks work by implementing every component manually. Understand forward propagation, backpropagation, and weight updates without relying on high-level libraries. Build fully connected neural networks step by step. Strengthen your understanding of deep learning fundamentals. Perfect for learners who want to master the core concepts.
Master enterprise-grade AI engineering using production-ready architectures, distributed model training, GPU acceleration, transformer networks, vector embeddings, and scalable inference pipelines. Implement TensorFlow, PyTorch, Hugging Face, CUDA, ONNX Runtime, TensorRT, and modern MLOps workflows. Design high-performance solutions with RAG, semantic search, FAISS, Pinecone, LangChain, Kubernetes, and cloud-native deployment strategies. Develop optimized, production-ready AI applications following industry best practices for scalability, observability, security, and performance.
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