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The Point Processing Toolkit (pptk) is a Python package for visualizing and processing 2-d/3-d point clouds.
An implementation of model parallel autoregressive transformers on GPUs, based on the Megatron and DeepSpeed libraries
Implementations of Amazon SageMaker-compatible custom containers for training.
Python programs, usually short, of considerable difficulty, to perfect particular skills.
This shows how to visualize the stack ensemble model trained by AutoGluon.
Example notebooks that show how to apply machine learning, deep learning and reinforcement learning in Amazon SageMaker
An efficient video loader for deep learning with smart shuffling that's super easy to digest
Natural language processing & computer vision models optimized for AWS
Deep Clustering for Unsupervised Learning of Visual Features
Medical Imaging, Denoising Autoencoder, Sparse Denoising Autoencoder (SDAE) End-to-end and Layer Wise Pretraining
Streamlit — A faster way to build and share data apps.
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Automatic architecture search and hyperparameter optimization for PyTorch
AWS ParallelCluster is an AWS supported Open Source cluster management tool to deploy and manage HPC clusters in the AWS cloud.
Toolkit for running PyTorch training scripts on SageMaker. Dockerfiles used for building SageMaker Pytorch Containers are at https://github.com/aws/deep-learning-containers.
Original Apollo 11 Guidance Computer (AGC) source code for the command and lunar modules.
Image based Anomaly Detection with Amazon SageMaker