Topic: "amazon-sagemaker-lab"
yoshitomo-matsubara/torchdistill
A coding-free framework built on PyTorch for reproducible deep learning studies. PyTorch Ecosystem. 🏆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.
Language: Python - Size: 10.5 MB - Last synced at: 2 days ago - Pushed at: 2 days ago - Stars: 1,499 - Forks: 133

aws/studio-lab-examples
Example notebooks for working with SageMaker Studio Lab. Sign up for an account at the link below!
Language: Jupyter Notebook - Size: 33.9 MB - Last synced at: 2 days ago - Pushed at: 9 months ago - Stars: 713 - Forks: 207

aws-samples/aws-ml-enablement-workshop
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
Language: Jupyter Notebook - Size: 107 MB - Last synced at: 25 days ago - Pushed at: 5 months ago - Stars: 518 - Forks: 55

icoxfog417/mlnote-note
機械学習帳を学ぶノート
Language: Jupyter Notebook - Size: 14.6 MB - Last synced at: about 1 month ago - Pushed at: over 2 years ago - Stars: 220 - Forks: 8

aws-sagemaker-jp/awesome-studio-lab-jp
SageMaker Studio Labの教材を紹介するリポジトリ。
Size: 4.64 MB - Last synced at: 3 days ago - Pushed at: 12 months ago - Stars: 97 - Forks: 3

SatelliteVu/SatelliteVu-AWS-Disaster-Response-Hackathon
Satellite Vu submission for the AWS Disaster Response hackathon
Language: Jupyter Notebook - Size: 39.8 MB - Last synced at: 6 days ago - Pushed at: about 3 years ago - Stars: 54 - Forks: 9

icoxfog417/datascience-template
Data science project template
Language: Jupyter Notebook - Size: 20.5 KB - Last synced at: about 1 month ago - Pushed at: over 2 years ago - Stars: 20 - Forks: 4

SrzStephen/DisaVu
A disaster response solution that helps allocate resources to where they're needed.
Language: Jupyter Notebook - Size: 9.44 MB - Last synced at: 28 days ago - Pushed at: almost 3 years ago - Stars: 19 - Forks: 4

machinelearnear/use-gradio-streamlit-sagemaker-studiolab
Language: Jupyter Notebook - Size: 1.12 MB - Last synced at: about 1 year ago - Pushed at: about 3 years ago - Stars: 15 - Forks: 0

machinelearnear/open-hf-spaces-in-studiolab
template for duplicating and executing Hugging Face Spaces either on SM Studio Lab, Google Colab, or locally.
Language: Jupyter Notebook - Size: 55.7 KB - Last synced at: about 1 year ago - Pushed at: over 2 years ago - Stars: 13 - Forks: 2

machinelearnear/video-super-resolution-youtube
Language: Jupyter Notebook - Size: 3.55 MB - Last synced at: about 1 year ago - Pushed at: about 3 years ago - Stars: 13 - Forks: 2

machinelearnear/large-scale-object-detection-with-sahi-detectron2
Language: Jupyter Notebook - Size: 4.33 MB - Last synced at: about 1 year ago - Pushed at: about 3 years ago - Stars: 12 - Forks: 3

machinelearnear/long-audio-transcription-spanish
Language: Jupyter Notebook - Size: 95.6 MB - Last synced at: about 1 year ago - Pushed at: about 3 years ago - Stars: 6 - Forks: 2

machinelearnear/amazon-textract-workbench
Language: Jupyter Notebook - Size: 8.35 MB - Last synced at: about 1 year ago - Pushed at: about 3 years ago - Stars: 5 - Forks: 0

aws-samples/aws-esg-evaluation-handson
Machine Learning for ESG evaluation
Language: Jupyter Notebook - Size: 27.2 MB - Last synced at: about 2 hours ago - Pushed at: almost 3 years ago - Stars: 4 - Forks: 1

machinelearnear/detic-detecting-20k-classes-using-image-level-supervision
Language: Jupyter Notebook - Size: 7.67 MB - Last synced at: about 1 year ago - Pushed at: about 3 years ago - Stars: 4 - Forks: 1

machinelearnear/sagemaker-studio-lab-quickstart
Language: Jupyter Notebook - Size: 1.59 MB - Last synced at: about 1 year ago - Pushed at: about 3 years ago - Stars: 4 - Forks: 1

Ashleshk/Practical-Data-Science-on-the-AWS-Cloud-Specialization
@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.
Language: Jupyter Notebook - Size: 7.39 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 3 - Forks: 1

machinelearnear/asr-restore-punctuation-summarization-biomedical-ehr
Language: Jupyter Notebook - Size: 34.2 KB - Last synced at: about 1 year ago - Pushed at: almost 3 years ago - Stars: 3 - Forks: 2

machinelearnear/custom-segmentation-model-with-icevision-openimages
Language: Jupyter Notebook - Size: 33.8 MB - Last synced at: about 1 year ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 1

machinelearnear/openai-glide-text2im
Language: Jupyter Notebook - Size: 2.5 MB - Last synced at: about 1 year ago - Pushed at: about 3 years ago - Stars: 1 - Forks: 3

machinelearnear/extract-info-by-doc-geometry-aws-textract
Language: Jupyter Notebook - Size: 3.13 MB - Last synced at: about 1 year ago - Pushed at: about 3 years ago - Stars: 1 - Forks: 0

machinelearnear/este-mate-no-existe
Language: Python - Size: 1.03 MB - Last synced at: about 1 year ago - Pushed at: about 3 years ago - Stars: 0 - Forks: 0
