Alternatives and similar repositories for bootcamp-bringing-ML-models-into-production-intermediary-jun-aug2021

Users that are interested in bootcamp-bringing-ML-models-into-production-intermediary-jun-aug2021 are comparing it to the libraries listed below

• KishManani / PyDataLondon2022
  Slides for "Feature engineering for time series forecasting" talk
  ☆61Updated 2 years ago
• dvaughan79 / analyticalskillsbook
  Code for the book Analytical Skills for AI and Data Science
  ☆47Updated 5 years ago
• PacktPublishing / Cleaning-Data-for-Effective-Data-Science
  Cleaning Data for Effective Data Science, published by Packt
  ☆100Updated 2 weeks ago
• tklouie / PyData_LA_2018
  Added repo for PyData LA 2018 tutorial
  ☆88Updated 6 years ago
• dmatrix / mlflow-workshop-part-1
  Partly lecture and partly a hands-on tutorial and workshop, this is a three part series on how to get started with MLflow. In this three …
  ☆240Updated 5 years ago
• carl24k / fight-churn
  Code from the book Fighting Churn With Data
  ☆297Updated last month
• PacktPublishing / Machine-Learning-Engineering-with-Python
  Machine Learning Engineering with Python
  ☆185Updated 2 weeks ago
• datarobot-community / tutorials-for-data-scientists
  ☆79Updated 2 years ago
• derevirn / pycaret-book
  Repository for the book Simplifying Machine Learning with PyCaret.
  ☆66Updated 2 years ago
• khuyentran1401 / customer_segmentation
  An end-to-end project on customer segmentation
  ☆83Updated 2 years ago
• trainindata / testing-and-monitoring-ml-deployments
  Example project for the course "Testing & Monitoring Machine Learning Model Deployments"
  ☆136Updated last year
• catherinenelson1 / SEforDS
  Code for the book "Software Engineering for Data Scientists"
  ☆96Updated last week
• PacktPublishing / EngineeringMLOps
  Engineering MLOps, published by Packt
  ☆188Updated 2 weeks ago
• PacktPublishing / Hands-On-Gradient-Boosting-with-XGBoost-and-Scikit-learn
  Hands-On Gradient Boosting with XGBoost and Scikit-learn Published by Packt
  ☆212Updated 2 weeks ago
• gaganmanku96 / Docker-Tutorial---Data-Scientists
  ☆27Updated 5 years ago
• BenWilson2 / ML-Engineering
  Reference code base for ML Engineering, Manning Publications
  ☆132Updated 4 years ago
• PacktPublishing / Machine-Learning-Engineering-with-MLflow
  Machine Learning Engineering with MLflow, published by Packt
  ☆117Updated 2 weeks ago
• datarobot-community / examples-for-data-scientists
  ☆64Updated last year
• juanitorduz / ml_prod_tutorial
  Explore tips and tricks to deploy machine learning models with Docker.
  ☆13Updated 2 years ago
• RamiKrispin / ai-dev-2024-ml-workshop
  Materials for the AI Dev 2024 conference workshop "Deploy and Monitor ML Pipelines with Python, Open Source, and Free Applications"
  ☆94Updated this week
• harnav / pydata-docker-tutorial
  Tutorial given at PyData LA 2018
  ☆97Updated last year
• khuyentran1401 / reproducible-data-science
  Tutorials on creating a reproducible and maintainable data science project
  ☆148Updated 3 years ago
• yoonhwang / hands-on-data-science-for-marketing
  ☆26Updated 4 years ago
• ewharton / ab-testing-resources
  ☆84Updated last year
• KishManani / DataTalksClub2022
  Slides for "Feature engineering for time series forecasting" talk for DataTalks.Club given in August 2022.
  ☆25Updated 2 years ago
• solegalli / Python-Feature-Engineering-Cookbook-First-Edition
  ☆32Updated last year
• RCdeWit / dtc-workshop
  Example project with a CNN to train a Pokémon type classifier, adapted for DTC workshop
  ☆36Updated last year
• hamedonline / ml-workflow
  A hands-on case study for demonstrating the stages involved in a machine learning project, from EDA to production.
  ☆38Updated 2 years ago
• solegalli / deploying-machine-learning-models
  Example Repo for the Udemy Course "Deployment of Machine Learning Models"
  ☆20Updated 5 years ago
• RamiKrispin / pydata-ny-ga-workshop
  Materials for the Deploy and Monitor ML Pipelines with Python, Docker and GitHub Actions workshop at the PyData NYC 2024 conference
  ☆81Updated this week