Deep learning is a subset of machine learning that uses neural networks with many hidden layers to automatically discover patterns in raw data. Unlike classical ML algorithms that rely on hand-crafted features, deep neural networks learn hierarchical representations — extracting simple features first (edges, syllables), then combining them into increasingly abstract concepts (faces, meaning). In … Read more
A neural network is a machine-learning model composed of layers of interconnected nodes (neurons) that learn to map inputs to outputs by adjusting numerical weights and biases during training. Each neuron computes a weighted sum of its inputs, adds a bias, and passes the result through a non-linear activation function. y = σ(Σ wᵢxᵢ + … Read more
An LLM (Large Language Model) is an AI system built on the transformer architecture that processes, understands, and generates human-like text by predicting the next token in a sequence. Trained on trillions of tokens from books, websites, and code repositories, LLMs such as GPT-4, Claude, and Llama 3 power applications ranging from conversational assistants and code … Read more