leehanchung / awesome-full-stack-machine-learning-coursesLinks
Curated list of publicly accessible machine learning engineering courses from CalTech, Columbia, Berkeley, MIT, and Stanford.
☆481Updated 3 months ago
Alternatives and similar repositories for awesome-full-stack-machine-learning-courses
Users that are interested in awesome-full-stack-machine-learning-courses are comparing it to the libraries listed below
Sorting:
- Software Architecture for ML engineers☆413Updated 3 years 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…☆183Updated 3 years ago
- FREE ML Courses from Top Universities☆252Updated this week
- A curated list of all the Awesome --Topic Name-- lists I've found till date relevant to Data lifecycle, ML and DL.☆341Updated last year
- Complete deep learning project developed in Full Stack Deep Learning, 2022 edition. Generated automatically from https://github.com/full-…☆478Updated last year
- 💁 Awesome Treasure of Transformers Models for Natural Language processing contains papers, videos, blogs, official repo along with colab…☆1,049Updated last month
- 🤓 A curated awesome list of Machine Learning Engineering resources. Feel free to contribute!☆295Updated 10 months ago
- Curated list of technical blogs on machine learning · AI/ML/DL/CV/NLP/MLOps☆268Updated this week
- Notes for Machine Learning Engineering for Production (MLOps) Specialization course by DeepLearning.AI & Andrew Ng☆371Updated 2 years ago
- 📌 Papers, guides, and mentor interviews on applying machine learning for ApplyingML.com—the ghost knowledge of machine learning.☆203Updated last year
- This repository offers a goldmine of materials for students of computer vision, natural language processing, and machine learning operati…☆421Updated 2 years ago
- Code and files to go along with CS329s machine learning model deployment tutorial.☆609Updated 2 years ago
- Blogs on Machine Learning and Deep learning☆114Updated 3 years ago
- Construct a modern data stack and orchestration the workflows to create high quality data for analytics and ML applications.☆226Updated 3 years ago
- Source for https://fullstackdeeplearning.com☆1,256Updated 4 months ago
- Build, train, deploy, scale and maintain deep learning models. Understand ML infrastructure and MLOps using hands-on examples.☆1,182Updated 2 years ago
- A book containing step by step instructions to train deep learning models for a variety of tasks☆37Updated last year
- This repo contains my solutions to “Introduction to Machine Learning Interviews” by Chip Huyen.☆170Updated last year
- Complete deep learning project developed in Full Stack Deep Learning, Spring 2021☆447Updated 3 years ago
- A collection of useful resources for Machine Learning System Design☆71Updated 4 years ago
- 🛠 MLOps end-to-end guide and tutorial website, using IBM Watson, DVC, CML, Terraform, Github Actions and more.☆315Updated last year
- Full Stack Deep Learning Online Course☆903Updated 4 years ago
- 📝 Design doc template & examples for machine learning systems (requirements, methodology, implementation, etc.)☆619Updated 2 years ago
- Preparation for Machine Learning Interview☆187Updated 10 months ago
- Exercises and supplementary material for the machine learning operations course at DTU.☆731Updated this week
- A roadmap for those looking to start or expand a career in the data community☆305Updated last month
- GitHub Repo with various ML/AI/DS resources that I find useful☆464Updated last year
- ☆36Updated 4 years ago
- How to become a data scientist in 30 days☆213Updated 3 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…☆157Updated 2 years ago