Tag: Deep Learning

Explains the Transformer architecture and attention mechanisms, revolutionizing NLP.

Learn about embeddings, vector databases, and semantic search to build advanced AI applications.

Learn how to optimize and deploy machine learning models for real-world applications, focusing on latency, throughput, cost, edge …

An in-depth look at the hardware that powers AI models, including CPUs, GPUs, and accelerators.

Learn how to systematically test, track, and debug machine learning models with Experimentation, Tracking & Debugging.

Learn to build a custom image classifier from scratch using PyTorch and transfer learning techniques.

Learn how to efficiently load, preprocess, and feed data to your models using TensorFlow's tf.data API.

A comprehensive guide to advanced Python programming, covering clean code principles, performance optimization, concurrency with asyncio, …

A comprehensive guide to Large Language Model (LLM) quantization, covering its principles, various techniques (4-bit, 8-bit, GGUF), …

A comprehensive guide to Deep Learning with PyTorch, covering foundational tensor operations, neural network construction, custom training, …

A comprehensive guide to Large Language Model (LLM) pre-training and fine-tuning concepts, covering Supervised Fine-tuning (SFT), …

A comprehensive and practical guide to MLOps and LLMOps principles and practices for managing the lifecycle of Large Language Models and …