The DBT of ML, as Aligned describes data dependencies in ML systems, and reduce technical data debt
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Updated
May 20, 2024 - Python
The DBT of ML, as Aligned describes data dependencies in ML systems, and reduce technical data debt
Prefect is a workflow orchestration tool empowering developers to build, observe, and react to data pipelines
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
These are my personal notes regarding Machine Learning DevOps stuff
Designing IT and ML Applications using Systems Thinking Approach at IIT Bhilai (CS559)
Fire up your models with the flame 🔥
An open-source ML pipeline development platform
A curated list of articles that cover the software engineering best practices for building machine learning applications.
Find the samples, in the test data, on which your (generative) model makes mistakes.
This machine learning pipeline project aims to develop an ML model to identify bank customer churn.
This GitHub repository showcases the implementation of a comprehensive end-to-end MLOps pipeline using Amazon SageMaker pipelines to deploy and manage 100x machine learning models. The pipeline covers data pre-processing, model training/re-training, hyperparameter tuning, data quality check,model quality check, model registry, and model deployment.
A list of interesting bookmarks, blogs, channels, papers, and anything that can be considered as a day to day reference for an AI, DS, ML, or DL practioner. [WIP]
A library of computer vision models and a streamlined framework for training them.
This machine learning pipeline project aims to develop an ML model to identify customer sentiment from French-language tweets on social media.
The universal data connector
Slides of my talk "Is Your ML Model Trustworthy?" at the MLOps World Conference on the 16th of June 2021.
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