AI frameworks are essential tools that simplify the development, training, and deployment of machine learning models. This blog explores most AI frameworks like TensorFlow, PyTorch, Keras, and Hugging Face, breaking down their strengths, community support, and ideal use cases. Learn how to choose the right framework based on your project goals, technical expertise, and scalability needs. We also cover advanced features like distributed training, autoML, and model interpretability. Whether you’re a data scientist or developer, understanding these frameworks helps accelerate your AI projects and improves model performance. Dive into comparisons, best practices, and real-world applications to make an informed decision for your next AI build.