Examples on how to train models with SageMaker.

Algorithms

• Image processing
  • image_classification
  • object_detection
  • semantic_segmentation
• Text processing
  • blazingtext
  • lda
  • ntm
  • seq2seq
• Time series processing
  • deepar
  • linear_learner
• Supervised learning algorithms
  • factorization_machines
  • knn
  • linear_learner
  • xgboost
• Unsupervised learning algorithms
  • ip_insights
  • kmeans
  • pca
  • rcf
• Feature engineering
  • object2vec

Bring your own container

• PyTorch
• Scikit
• TensorFlow

Data types

• Image
• Tabular
• Text
• Time series

Debugger

• Get started with SageMaker Debugger
• Real-time analysis
• MXNet
• PyTorch
• TensorFlow
• XGBoost
• Bring your own container

Distributed Training

• Apache MXNet
• PyTorch
• TensorFlow

Experiments

• Get started with Experiments
• Airflow workflow tracking
• Search

Frameworks

• Apache MXNet
• Deep Graph Library
• PyTorch
• R
• Scikit-learn
• TensorFlow

Hyperparameter tuning

• Apache MXNet
• PyTorch
• R
• TensorFlow
• XGBoost
• Use cases

Management features

• Early stopping
• Spot training
• Warm start

Reinforcement learning

• Get started with RL
• AWS DeepRacer
• Cart pole
• Contextual bandits
• Roboschool
• Use cases