Machine Learning Frameworks are software libraries or tools that simplify the process of building and deploying machine learning models. They provide pre-built functions and algorithms, allowing developers to focus on designing their models rather than coding everything from scratch. Popular frameworks include TensorFlow, PyTorch, and Scikit-learn. These frameworks support various tasks, such as data preprocessing, model training, and evaluation. They often come with extensive documentation and community support, making it easier for both beginners and experienced practitioners to implement machine learning solutions efficiently.