The AI lifecycle encompasses data gathering, modeling, and application. Raw data, including structured, unstructured, and real-time data, is processed using machine learning algorithms (supervised, unsupervised, etc.) and models (deep learning, NLP, etc.). Tools and platforms help with data handling and model deployment. AI applications include predictive analytics, image recognition, and natural language processing.
