Alternatives and similar repositories for Made-With-ML

Users that are interested in Made-With-ML are comparing it to the libraries listed below

• dmatrix / ray-core-tutorial
  Introduction to Ray Core Design Patterns and APIs.
  ☆71Updated last year
• scalingpythonml / scalingpythonml
  Scaling Python Machine Learning
  ☆50Updated 2 years ago
• DerwenAI / ray_tutorial
  An introductory tutorial about leveraging Ray core features for distributed patterns.
  ☆78Updated 2 years ago
• jacopotagliabue / recs-at-resonable-scale
  Recommendations at "Reasonable Scale": joining dataOps with recSys through dbt, Merlin and Metaflow
  ☆240Updated 2 years ago
• unionai-oss / llm-fine-tuning
  Fine-tuning LLMs on Flyte and Union Cloud
  ☆28Updated last year
• jacopotagliabue / post-modern-stack
  Joining the modern data stack with the modern ML stack
  ☆199Updated 2 years ago
• machine-learning-apps / actions-ml-cicd
  A Collection of GitHub Actions That Facilitate MLOps
  ☆208Updated 2 years ago
• eugeneyan / python-collab-template
  🛠 Python project template with unit tests, code coverage, linting, type checking, Makefile wrapper, and GitHub Actions.
  ☆149Updated last year
• shreyashankar / toy-ml-pipeline
  Toy example of an applied ML pipeline for me to experiment with MLOps tools.
  ☆208Updated 3 years ago
• anyscale / ray-summit-2023-training
  ☆87Updated last year
• zenml-io / mlstacks
  A series of Terraform based recipes to provision popular MLOps stacks on the cloud.
  ☆255Updated 11 months ago
• loglabs / mltrace
  Coarse-grained lineage and tracing for machine learning pipelines.
  ☆469Updated 2 years ago
• GokuMohandas / testing-ml
  Learn how to create reliable ML systems by testing code, data and models.
  ☆89Updated 3 years ago
• eugeneyan / papermill-mlflow
  🧪 Simple data science experimentation & tracking with jupyter, papermill, and mlflow.
  ☆183Updated last year
• eugeneyan / testing-ml
  🔍 Minimal examples of machine learning tests for implementation, behaviour, and performance.
  ☆263Updated 3 years ago
• scalingpythonml / scaling-python-with-ray
  Serverless Python with Ray
  ☆58Updated 2 years ago
• modzy / model-deployment-checklist
  An efficient, to-the-point, and easy-to-use checklist to following when deploying an ML model into production.
  ☆30Updated 2 years ago
• sayakpaul / ml-deployment-k8s-fastapi
  This project shows how to serve an ONNX-optimized image classification model as a web service with FastAPI, Docker, and Kubernetes.
  ☆221Updated 3 years ago
• ray-project / xgboost_ray
  Distributed XGBoost on Ray
  ☆149Updated last year
• outerbounds / dsbook
  Code samples for the Effective Data Science Infrastructure book
  ☆115Updated 2 years ago
• zenml-io / zenml-gitflow
  A repository that showcases how you can use ZenML with Git
  ☆70Updated last month
• aporia-ai / mlops.toys
  🎲 A curated list of MLOps projects, tools and resources
  ☆185Updated last year
• operatorai / modelstore
  🏬 modelstore is a Python library that allows you to version, export, and save a machine learning model to your filesystem or a cloud sto…
  ☆397Updated 8 months ago
• thoughtworks / mlops-platforms
  Compare MLOps Platforms. Breakdowns of SageMaker, VertexAI, AzureML, Dataiku, Databricks, h2o, kubeflow, mlflow...
  ☆394Updated 2 years ago
• rocket9-code / mlflow-deployment-controller
  Listens MLFlow model registry changes and deploy models based on configurations
  ☆20Updated 2 years ago
• jacopotagliabue / FREE_7773
  Materials for my 2021 NYU class on NLP and ML Systems (Master of Engineering).
  ☆96Updated 2 years ago
• iterative / demo-bank-customer-churn
  Demo DVC project training a classification model on tabular data
  ☆41Updated last year
• jacopotagliabue / no-ops-machine-learning
  A PaaS End-to-End ML Setup with Metaflow, Serverless and SageMaker.
  ☆37Updated 4 years ago
• adriangonz / mlflow-talk
  End to End example integrating MLFlow and Seldon Core
  ☆52Updated 4 years ago
• radekosmulski / nvt_op_examples
  ☆27Updated 3 years ago