AI & ML Development

Machine learning is a subset of AI that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. ML focuses on the development of computer programs that can access data and use it to learn for themselves.

AI is a broader concept concerning machines designed to act intelligently, while ML is a specific subset of AI that trains a machine how to learn. ML is one way we are achieving AI.

Supervised learning: The model is trained on a labeled dataset, which means it has an input parameter and an output parameter.
Unsupervised learning: The model works on unlabeled data without a given outcome.
Reinforcement learning: The model learns to make decisions based on trial and error, receiving rewards or penalties.

Python is widely recognized as the leading language due to its simplicity and the extensive availability of AI and ML libraries, such as TensorFlow, Keras, and Scikit-learn. Other useful languages include R for statistical analysis, Java for system integration, and C++ for performance in ML operations.