Probabilistic time series modeling in Python
A library for training and deploying machine learning models on Amazon SageMaker
pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, Neptune, OpenSearch, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL).
Application implementation with business use cases for safely utilizing generative AI in business operations
組織横断的にチームを組成し、機械学習による成長サイクルを実現する計画を立てるワークショップ
AWS Generative AI CDK Constructs are sample implementations of AWS CDK for common generative AI patterns.
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Train machine learning models within a 🐳 Docker container using 🧠 Amazon SageMaker.
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
A coding-free framework built on PyTorch for reproducible deep learning studies. PyTorch Ecosystem. 🏆26 knowledge distillation methods presented at TPAMI, CVPR, ICLR, ECCV, NeurIPS, ICCV, AAAI, etc are implemented so far. 🎁 Trained models, training logs and configurations are available for ensuring the reproducibiliy and benchmark.