Alternatives and similar repositories for build-and-deploy-real-time-feature-pipeline

Users that are interested in build-and-deploy-real-time-feature-pipeline are comparing it to the libraries listed below

• Paulescu / real-time-ohlc-with-bytewax
  Fetch, transform and plot real-time OHLC data from Coinbase using Bytewax, Bokeh and Streamlit
  ☆129Updated last year
• Paulescu / bytewax-hopsworks-example
  Compute and store real-time features for crypto trading using Bytwax (stream processing) and Hopsworks (Feature Store)
  ☆145Updated 2 years ago
• MatejFrnka / ScalableML-project
  ☆110Updated 2 years ago
• logicalclocks / hopsworks-tutorials
  Tutorials for the Hopsworks Platform
  ☆306Updated last month
• Paulescu / real-time-data-pipelines-in-python
  Real-time Feature Pipelines in Python ⚡
  ☆282Updated last year
• Paulescu / incremental-ml-training-and-serving
  Incremental ML learning in the real-world
  ☆69Updated 6 months ago
• BexTuychiev / tricking-data-science
  A book of subtle code tricks and gem resources for all things data, machine learning and deep learning.
  ☆168Updated last year
• javieryanzon / bike_sharing_demand_predictor
  Project bike sharing predictor
  ☆80Updated last month
• zenml-io / zenml-projects
  A repository for all ZenML projects that are specific production use-cases.
  ☆277Updated last month
• erno98 / ID2223
  ☆24Updated 2 years ago
• khuyentran1401 / cicd-mlops-demo
  Demo for CI/CD in a machine learning project
  ☆112Updated 2 years ago
• manuelgilm / mlflow_for_ml_dev
  Repository with code examples of mlflow
  ☆222Updated last month
• karan842 / mlops-best-practices
  Practical guide to build end-to-end machine learning pipeline and deploy your model in production,
  ☆72Updated 2 years ago
• PacktPublishing / Practical-Deep-Learning-at-Scale-with-MLFlow
  Practical Deep Learning at Scale with MLFlow, published by Packt
  ☆162Updated 3 weeks ago
• marvelousmlops / mlops_maturity_assessment
  MLOps maturity assessment
  ☆61Updated 2 years ago
• Paulescu / ml-rest-api-caching
  How to serve ML predictions 100x faster
  ☆59Updated last year
• baniasbaabe / learning-data-science
  Curated collection of awesome resources and tutorials for mastering Data Science, Machine Learning, Deep Learning, and Python.
  ☆51Updated 11 months ago
• SebastianoMeneghin / sml-project-2023-manfredi-meneghin
  Scalable Machine Learning and Deep Learning, Final Project, 2023/2024
  ☆245Updated 10 months ago
• ashishpatel26 / LLM-Engineering-Crash-Course
  LLM Engineering CrashCourse
  ☆101Updated last year
• zenml-io / zenbytes
  A simple guide to MLOps through ZenML and its various integrations.
  ☆187Updated last year
• Paulescu / real-time-technical-indicators
  Learn to build a modular real-time feature pipeline, so you avoid Offline-Online Feature Skew, and your deployed ML models work as expect…
  ☆44Updated last year
• hamzafarooq / advanced-llms-course
  Code files for advanced LLM Course
  ☆214Updated last year
• PacktPublishing / Machine-Learning-Engineering-with-Python
  Machine Learning Engineering with Python
  ☆185Updated 3 weeks ago
• PacktPublishing / Machine-Learning-for-Imbalanced-Data
  Machine Learning for Imbalanced Data, published by Packt
  ☆277Updated 3 weeks ago
• marvelousmlops / mlops-roadmap-2024
  ☆358Updated last year
• GokuMohandas / data-engineering
  Construct a modern data stack and orchestration the workflows to create high quality data for analytics and ML applications.
  ☆227Updated 3 years ago
• khuyentran1401 / customer_segmentation
  An end-to-end project on customer segmentation
  ☆83Updated 2 years ago
• PacktPublishing / EngineeringMLOps
  Engineering MLOps, published by Packt
  ☆188Updated 3 weeks ago
• PacktPublishing / Machine-Learning-Engineering-with-Python-Second-Edition
  ☆245Updated 3 weeks ago
• 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
  ☆102Updated 2 years ago