PacktPublishing / Practical-Deep-Learning-at-Scale-with-MLFlow

Related projects ⓘ

Alternatives and complementary repositories for Practical-Deep-Learning-at-Scale-with-MLFlow

• khuyentran1401 / cicd-mlops-demo
  Demo for CI/CD in a machine learning project
  ☆93Updated last year
• PacktPublishing / Machine-Learning-for-Streaming-Data-with-Python
  Machine Learning for Streaming Data with Python, published by Packt
  ☆68Updated last year
• khuyentran1401 / customer_segmentation
  An end-to-end project on customer segmentation
  ☆82Updated last year
• PacktPublishing / Comet-for-Data-Science
  Comet for Data Science, published by Packt
  ☆42Updated last year
• PacktPublishing / Machine-Learning-Engineering-with-MLflow
  Machine Learning Engineering with MLflow, published by Packt
  ☆114Updated 4 months ago
• PacktPublishing / EngineeringMLOps
  Engineering MLOps, published by Packt
  ☆177Updated last year
• PacktPublishing / Applied-Machine-Learning-Explainability-Techniques
  Applied Machine Learning Explainability Techniques, published by Packt
  ☆237Updated last year
• AntonisCSt / Mlops_project_semicon
  A project from the ml_ops Zoomcamp (DataTalks) using Semiconductor data
  ☆22Updated 2 years ago
• ThinamXx / MLOps
  The repository contains a list of projects which I will work on while learning and implementing MLOps.
  ☆79Updated last year
• BenWilson2 / ML-Engineering
  Reference code base for ML Engineering, Manning Publications
  ☆122Updated 3 years ago
• soumik12345 / mlops-zoomcamp-wandb
  ☆31Updated last year
• khuyentran1401 / Machine-learning-pipeline
  Example machine learning pipeline with MLflow and Hydra
  ☆87Updated last year
• zenml-io / zenbytes
  A simple guide to MLOps through ZenML and its various integrations.
  ☆183Updated 9 months ago
• iterative / magnetic-tiles-defect
  Demo Computer Vision Project
  ☆59Updated last year
• hamedonline / ml-workflow
  A hands-on case study for demonstrating the stages involved in a machine learning project, from EDA to production.
  ☆37Updated last year
• ziritrion / ml-zoomcamp
  ML Zoomcamp fall 2021 homework and stuff
  ☆60Updated 2 years ago
• trojrobert / MLOps_roadmap_and_curriculum
  Curriculum and roadmap from 0 to Mastery for MLOps. Adding value to your machine learning model by deploying it for people to use it to s…
  ☆184Updated 2 years ago
• marvelousmlops / mlops_maturity_assessment
  MLOps maturity assessment
  ☆57Updated last year
• outerbounds / dsbook
  Code samples for the Effective Data Science Infrastructure book
  ☆110Updated last year
• BexTuychiev / tricking-data-science
  A book of subtle code tricks and gem resources for all things data, machine learning and deep learning.
  ☆165Updated 2 months ago
• PacktPublishing / Production-Ready-Applied-Deep-Learning
  Production-Ready Applied Deep Learning
  ☆87Updated last year
• alvarobartt / serving-tensorflow-models
  Serving TensorFlow models with TensorFlow Serving
  ☆44Updated 2 years ago
• rafiqhasan / auto-tensorflow
  Build Low Code Automated Tensorflow explainable models in just 3 lines of code. Library created by: Hasan Rafiq - https://www.linkedin.co…
  ☆181Updated last year
• Paulescu / build-and-deploy-real-time-feature-pipeline
  Develop and deploy a real-time feature pipeline in Python, using Bytewax 🐝 and Hopsworks Feature Store.
  ☆125Updated last year
• ml-for-high-risk-apps-book / Machine-Learning-for-High-Risk-Applications-Book
  Official code repo for the O'Reilly Book - Machine Learning for High-Risk Applications
  ☆97Updated last year
• khuyentran1401 / reproducible-data-science
  Tutorials on creating a reproducible and maintainable data science project
  ☆138Updated 2 years ago
• khuyentran1401 / employee-future-prediction
  Demo for Using GitHub Actions in MLOps
  ☆40Updated 2 years ago
• noahgift / mlflow-project-best-practices
  An example MLFlow project
  ☆48Updated 2 years ago
• mlops-guide / dvc-gitactions
  Example project with a complete MLOps cycle: versioning data, generating reports on pull requests and deploying the model on releases wit…
  ☆45Updated 2 years ago
• GokuMohandas / testing-ml
  Learn how to create reliable ML systems by testing code, data and models.
  ☆83Updated 2 years ago