itsderek23 / lessons
📚 Learn ML with clean code, simplified math and illustrative visuals. As you learn, work on interesting projects and share them on https://madewithml.com for the community to discover and learn from!
☆12Updated 4 years ago
Related projects: ⓘ
- ☆91Updated 3 years ago
- This sample demonstrates how to setup an Amazon SageMaker MLOps end-to-end pipeline for Drift detection☆58Updated 11 months ago
- Amazon SageMaker MLOps deployment pipeline for A/B Testing of machine learning models.☆41Updated 3 years ago
- Example templates for the delivery of custom ML solutions to production so you can get started quickly without having to make too many de…☆66Updated 3 months ago
- A project template for developing BYOD docker images for use in Amazon SageMaker.☆19Updated 4 years ago
- CLI for building Docker images in SageMaker Studio using AWS CodeBuild.☆57Updated 2 years ago
- A recipe of SageMaker Ground Truth Lambdas to be used for creating labeling jobs with custom task type☆25Updated last year
- Serve scikit-learn, XGBoost, TensorFlow, and PyTorch models with AWS Lambda container images support.☆95Updated last month
- Hosting code-server on Amazon SageMaker☆50Updated 11 months ago
- ☆21Updated 4 years ago
- Sample Jupyter Notebooks for Amazon Augmented AI (A2I)☆69Updated 9 months ago
- SageMaker custom deployments made easy☆56Updated 8 months ago
- End to end Machine Learning with Amazon SageMaker☆37Updated 7 months ago
- This sample show you how to train BERT on Amazon Sagemaker using Spot instances☆31Updated 9 months ago
- Docker images that replicate the Amazon SageMaker Notebook instance.☆58Updated 2 years ago
- ☆57Updated 2 years ago
- MLOps workshop with Amazon SageMaker☆84Updated 6 months ago
- SageMaker specific extensions to TensorFlow.☆54Updated last month
- Build Train and Deploy your own custom container using AWS StepFunctions Data Science SDK☆22Updated 4 years ago
- Safe blue/green deployment of Amazon SageMaker endpoints using AWS CodePipeline, CodeBuild and CodeDeploy.☆104Updated last year
- This repo will teach you how to deploy an ML-powered web app to AWS Fargate from start to finish using Streamlit and AWS CDK☆102Updated 3 years ago
- Fairness Aware Machine Learning. Bias detection and mitigation for datasets and models.☆66Updated 5 months ago
- Custom docker container for Catboost on Amazon SageMaker☆13Updated last year
- Distributed training with SageMaker's script mode using Horovod distributed deep learning framework☆32Updated 4 years ago
- Over 60 example task UIs for Amazon Augmented AI (A2I)☆93Updated 3 years ago
- This is a sample solution for bringing your own ML models and inference code, and running them at scale using AWS serverless services.☆34Updated 9 months ago
- Tools to run Jupyter notebooks as jobs in Amazon SageMaker - ad hoc, on a schedule, or in response to events☆140Updated 11 months ago
- Build end-to-end Machine Learning pipeline to predict accessibility of playgrounds in NYC☆14Updated 4 years ago
- A curated list of references for Amazon SageMaker☆152Updated 8 months ago
- MLOps End-to-End Example using Amazon SageMaker Pipeline, AWS CodePipeline and AWS CDK☆112Updated this week