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
Artificial intelligence (AI) is the branch of computer science focused on building systems that perform tasks associated with human intelligence — learning, reasoning, planning, perception, and communication. Modern AI spans everything from rule-based expert systems and classical machine learning to deep neural networks and large language models, and it is governed by an evolving regulatory landscape including … Read more