Examples and tutorials on using SOTA computer vision models and techniques. Learn everything from old-school ResNet, through YOLO and object-detection transformers like DETR, to the latest models like Grounding DINO and SAM.

A coding-free framework built on PyTorch for reproducible deep learning studies. 🏆25 knowledge distillation methods presented at CVPR, ICLR, ECCV, NeurIPS, ICCV, etc are implemented so far. 🎁 Trained models, training logs and configurations are available for ensuring the reproducibiliy and benchmark.

Example notebooks for working with SageMaker Studio Lab. Sign up for an account at the link below!

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

機械学習帳を学ぶノート

SageMaker Studio Labの教材を紹介するリポジトリ。

Satellite Vu submission for the AWS Disaster Response hackathon

@DeepLearning.AI Practical Data Science Specialization brings together these disciplines using purpose-built ML tools in the AWS cloud. It has helped me to develop the practical skills to effectively deploy your data science projects and overcome challenges at each step of the ML workflow using Amazon SageMaker.

Data science project template

A disaster response solution that helps allocate resources to where they're needed.

template for duplicating and executing Hugging Face Spaces either on SM Studio Lab, Google Colab, or locally.

Machine Learning for ESG evaluation