Alternatives and similar repositories for AWS-Serverless-Data-Engineering-Pipeline

Users that are interested in AWS-Serverless-Data-Engineering-Pipeline are comparing it to the libraries listed below

• bodywork-ml / ml-pipeline-engineering
  Best practices for engineering ML pipelines.
  ☆36Updated 3 years ago
• data-max-hq / ab-testing-in-ml
  Deploy A/B testing infrastructure in a containerized microservice architecture for Machine Learning applications.
  ☆40Updated 8 months ago
• ds-muzalevskiy / sagemaker-docker-deploy
  ☆18Updated 3 years ago
• elleobrien / automatic_testing
  ☆21Updated 2 years ago
• jacopotagliabue / no-ops-machine-learning
  A PaaS End-to-End ML Setup with Metaflow, Serverless and SageMaker.
  ☆37Updated 4 years ago
• noahgift / aws-ml-guide
  [Video]AWS Certified Machine Learning-Specialty (ML-S) Guide
  ☆122Updated 8 months ago
• YisongZou / Flask-Salary-Predictor-with-Random-Forest-Algorithm
  In this project, we are going to use a random forest algorithm (or any other preferred algorithm) from scikit-learn library to help predi…
  ☆10Updated 4 years ago
• deliveryhero / pyconde2019-airflow-ml-workshop
  PyConDE & PyData Berlin 2019 Airflow Workshop: Airflow for machine learning pipelines.
  ☆47Updated 2 years ago
• noahgift / or
  Operations Research Algorithms
  ☆18Updated last year
• thejat / mlops-notebooks
  ☆66Updated 4 months ago
• noahgift / mlflow-project-best-practices
  An example MLFlow project
  ☆48Updated 8 months ago
• sejalv / serverless-ml-workshop
  Deployment of ML models with Serverless APIs (AWS Lambda) and Docker
  ☆25Updated 4 years ago
• monte-carlo-data / data-downtime-challenge
  ☆87Updated 2 years ago
• vincentclaes / datajob
  Build and deploy a serverless data pipeline on AWS with no effort.
  ☆111Updated 2 years ago
• edublancas / ml-testing
  🐍 Material for PyData Global 2021 Presentation: Effective Testing for Machine Learning Projects
  ☆82Updated 3 years ago
• noahgift / databricks-zero-to-mlops
  ☆27Updated 3 years ago
• eugeneyan / poc-docker-template
  Simple template showing how to set up docker for reproducible data science with Jupyter notebooks.
  ☆23Updated last year
• mlrun / demos
  End to end MLRun demos
  ☆93Updated last month
• aws-samples / amazon-sagemaker-drift-detection
  This sample demonstrates how to setup an Amazon SageMaker MLOps end-to-end pipeline for Drift detection
  ☆62Updated last year
• dmatrix / mlflow-workshop-part-3
  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 four p…
  ☆35Updated 5 years ago
• tecton-ai / apply-workshop-2022
  ☆17Updated 3 years ago
• jacobceles / intro-to-colab-pyspark-emr
  A tutorial that helps Big Data Engineers ramp up faster by getting familiar with PySpark dataframes and functions. It also covers topics …
  ☆20Updated 3 years ago
• 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
  ☆69Updated last month
• Spratiher9 / SparkDataset
  Instant search for and access to many datasets in Pyspark.
  ☆34Updated 2 years ago
• joelcthomas / modeldrift
  Capturing model drift and handling its response - Example webinar
  ☆108Updated 6 years ago
• scalingpythonml / scalingpythonml
  Scaling Python Machine Learning
  ☆49Updated 2 years ago
• eugeneyan / papermill-mlflow
  🧪 Simple data science experimentation & tracking with jupyter, papermill, and mlflow.
  ☆182Updated last year
• srivatsan88 / AI-Value-Realization-Framework
  This repository is to host template for calculating ROI on Artificial Intelligence projects
  ☆45Updated 6 years ago
• jacopotagliabue / FREE_7773
  Materials for my 2021 NYU class on NLP and ML Systems (Master of Engineering).
  ☆96Updated 2 years ago