AlexIoannides / ml-workflow-automation
Python Machine Learning (ML) project that demonstrates the archetypal ML workflow within a Jupyter notebook, with automated model deployment as a RESTful service on Kubernetes.
☆61Updated 2 years ago
Alternatives and similar repositories for ml-workflow-automation:
Users that are interested in ml-workflow-automation are comparing it to the libraries listed below
- Makes Interactive Chart Widget, Cleans raw data, Runs baseline models, Interactive hyperparameter tuning & tracking☆55Updated 3 years ago
- This repository is to host template for calculating ROI on Artificial Intelligence projects☆44Updated 5 years ago
- Explore tips and tricks to deploy machine learning models with Docker.☆13Updated last year
- Tips for Advanced Feature Engineering☆52Updated 4 years ago
- ☆18Updated 6 years ago
- Work for Mastering Large Datasets with Python☆18Updated 2 years ago
- A code-based tutorial for production level data streaming with PySpark plus Optimus for data cleaning, Confluent Kafka, & Apache Drill u…☆26Updated 5 years ago
- An example MLFlow project☆48Updated 2 months ago
- Pyspark in Google Colab: A simple machine learning (Linear Regression) model☆36Updated 5 years ago
- 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…☆34Updated 4 years ago
- Content for Applied ML Workshop @ DataHack Summit 2019☆25Updated 5 years ago
- ☆31Updated 9 months ago
- Blog post on ETL pipelines with Airflow☆23Updated 4 years ago
- Applied Machine Learning with Python☆78Updated 11 months ago
- Best practices for engineering ML pipelines.☆37Updated 2 years ago
- Predicting the Likelihood to Purchase a Financial Product Following a Direct Marketing Campaign☆27Updated 2 years ago
- The practical use-cases of how to make your Machine Learning Pipelines robust and reliable using Apache Airflow.☆52Updated 2 years ago
- Guide for applying Unit Testing in data-driven projects☆19Updated 4 years ago
- Pytest for Data Science Beginners☆58Updated 6 years ago
- Guide on creating an API for serving your ML model☆65Updated 2 years ago
- ☆40Updated 7 years ago
- A machine learning algorithm written to predict severity of insurance claim☆20Updated 8 years ago
- Data models, build data warehouses and data lakes, automate data pipelines, and worked with massive datasets.☆13Updated 5 years ago
- An end-to-end project on customer segmentation☆81Updated 2 years ago
- Study notes and demos.☆12Updated last year
- Companion Notebooks and Data for Data Science with Python and Dask from Manning Publications☆51Updated 4 years ago
- 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…☆38Updated 3 years ago
- Automated Data Science and Machine Learning library to optimize workflow.☆104Updated 2 years ago
- Using Kafka-Python to illustrate a ML production pipeline☆109Updated 2 years ago
- ☆18Updated 3 years ago