superlinear-ai / awesome-machine-learning-engineerLinks
🤓 A curated awesome list of Machine Learning Engineering resources. Feel free to contribute!
☆297Updated last year
Alternatives and similar repositories for awesome-machine-learning-engineer
Users that are interested in awesome-machine-learning-engineer are comparing it to the libraries listed below
Sorting:
- Software Architecture for ML engineers☆413Updated 3 years ago
- 📝 Design doc template & examples for machine learning systems (requirements, methodology, implementation, etc.)☆622Updated 2 years ago
- Curated list of publicly accessible machine learning engineering courses from CalTech, Columbia, Berkeley, MIT, and Stanford.☆486Updated 5 months ago
- The Fuzzy Labs guide to the universe of open source MLOps☆472Updated 5 months ago
- Curriculum and roadmap from 0 to Mastery for MLOps. Adding value to your machine learning model by deploying it for people to use it to s…☆184Updated 3 years ago
- 📌 Papers, guides, and mentor interviews on applying machine learning for ApplyingML.com—the ghost knowledge of machine learning.☆203Updated last year
- 🔍 Minimal examples of machine learning tests for implementation, behaviour, and performance.☆263Updated 3 years ago
- Notes for Machine Learning Engineering for Production (MLOps) Specialization course by DeepLearning.AI & Andrew Ng☆374Updated 2 years ago
- Complete deep learning project developed in Full Stack Deep Learning, 2022 edition. Generated automatically from https://github.com/full-…☆478Updated last year
- An end-to-end implementation of intent prediction with Metaflow and other cool tools☆872Updated 2 years ago
- A simple guide to MLOps through ZenML and its various integrations.☆187Updated last year
- A collection of useful resources for Machine Learning System Design☆71Updated 5 years ago
- Construct a modern data stack and orchestration the workflows to create high quality data for analytics and ML applications.☆228Updated 3 years ago
- An ongoing list of pandas quirks☆981Updated 2 years ago
- A detailed summary of "Designing Machine Learning Systems" by Chip Huyen. This book gives you and end-to-end view of all the steps requir…☆162Updated 2 years ago
- Blogs on Machine Learning and Deep learning☆114Updated 3 years ago
- Compilation of high-profile real-world examples of failed machine learning projects☆742Updated last year
- A series of Terraform based recipes to provision popular MLOps stacks on the cloud.☆255Updated last year
- Curated list of open source tooling for data-centric AI on unstructured data.☆731Updated last year
- A book of subtle code tricks and gem resources for all things data, machine learning and deep learning.☆169Updated last year
- Learn how to create reliable ML systems by testing code, data and models.☆89Updated 3 years ago
- Slides, scripts and materials for the Machine Learning in Finance Course at NYU Tandon, 2022☆525Updated 2 years ago
- Interview Questions and Answers for Machine Learning Engineer role☆116Updated 5 months ago
- Free Open-source ML observability course for data scientists and ML engineers. Learn how to monitor and debug your ML models in productio…☆98Updated last year
- Code and files to go along with CS329s machine learning model deployment tutorial.☆612Updated 2 years ago
- Build, train, deploy, scale and maintain deep learning models. Understand ML infrastructure and MLOps using hands-on examples.☆1,187Updated 2 years ago
- Practical Deep Learning at Scale with MLFlow, published by Packt☆162Updated last month
- This repo contains my solutions to “Introduction to Machine Learning Interviews” by Chip Huyen.☆174Updated last year
- Learn how to create, develop, and maintain a state-of-the-art MLOps code base☆599Updated last month
- Exercises and supplementary material for the machine learning operations course at DTU.☆731Updated this week