Artificial intelligence is the development of computer systems that can perform tasks that would typically require human intelligence.
Machine Learning Explained
Machine learning is a field of study that focuses on developing algorithms and models that enable computers to learn and make predictions or decisions without being explicitly programmed.
Deep Learning Explained
Deep learning is a subset of artificial intelligence that uses neural networks to mimic the human brain and make complex decisions.
Neural Networks Explained
Neural networks are computational models inspired by the human brain that can learn and make predictions based on complex patterns and data.
Computer Vision Explained
Computer vision is a field of science and technology that focuses on enabling computers to interpret and understand visual information from images or videos.
Reinforcement Learning Explained
Reinforcement learning is a branch of machine learning that focuses on training agents to make decisions based on trial and error in order to maximize rewards.
Transfer Learning Explained
Transfer learning is a technique in machine learning where knowledge gained from one task is applied to a different but related task.
Generative Adversarial Networks Explained
Generative adversarial networks (GANs) are a type of machine learning model that uses two neural networks, a generator and a discriminator, to generate realistic data and improve the quality of generated content.
Neural Architecture Search Explained
Neural architecture search is a method that automates the design of neural networks to optimize their performance and efficiency.
Autonomous Systems Explained
Autonomous systems refer to technologies that can perform tasks and make decisions without human intervention.