Discovering the built-in frameworks in Amazon SageMaker
SageMaker lets you train and deploy your models with the following machine learning and deep learning frameworks:
- Scikit-learn, undoubtedly the most widely used open source library for machine learning. If you're new to this topic, start here: https://scikit-learn.org.
- XGBoost, an extremely popular and versatile open source algorithm for regression, classification, and ranking problems (https://xgboost.ai). It's also available as a built-in algorithm, as presented in Chapter 4, Training Machine Learning Models. Using it in framework mode will give us more flexibility.
- TensorFlow, an extremely popular open source library for deep learning (https://www.tensorflow.org). SageMaker also supports the lovable Keras API (https://keras.io).
- PyTorch, another highly popular open source library for deep learning (https://pytorch.org). Researchers, in particular, enjoy its flexibility.
- Apache MXNet, an interesting...
