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awesome-full-stack-machine-learning-courses
Curated list of publicly accessible machine learning engineering courses from CalTech, Columbia, Berkeley, MIT, and Stanford.
https://github.com/leehanchung/awesome-full-stack-machine-learning-courses
Last synced: 5 days ago
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Math and Statistics
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Computer Science
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:books: Textbooks
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:school: Courses
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Artificial Intelligence
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Machine Learning
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:books: Textbooks
- Mathematics for Machine Learning
- Concise Machine Learning
- The Elements of Statistical Learning
- Pattern Recognition and Machine Learning
- Stanford CS229: Machine Learning
- Harvard CS 109A Data Science
- edX ColumbiaX: Machine Learning
- Berkeley CS294: Fairness in Machine Learning
- Google: Machine Learning Crash Course
- Probabilistic Machine Learning (Summer 2020)
- AutoML - Automated Machine Learning
- MIT: Data Centric AI
- Google: Applied Machine Learning Intensive
- Cornell Tech CS5785: Applied Machine Learning
- Mining of Massive Datasets
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Machine Learning Engineering
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:books: Textbooks
- Machine Learning Engineering
- Machine Learning System Design
- Microsoft Commercial Software Engineering ML Fundamentals
- Google Rules of ML
- The Twelve Factors App
- Feature Engineering and Selection: A Practical Approach for Predictive Models
- Continuous Delivery for Machine Learning
- Stanford: CS 329S: Machine Learning Systems Design
- CMU: Machine Learning in Production
- Andrew Ng: Bridging AI's Proof-of-Concept to Production Gap
- Facebook Field Guide to Machine Learning
- Udemy: Deployment of Machine Learning Models
- Udemy: The Complete Hands On Course To Master Apache Airflow
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Deep Learning Overview
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:books: Textbooks
- Dive into Deep Learning
- The Matrix Calculus You Need For Deep Learning
- Stanford CS 25: Transformers - 8-Y&list=PLoROMvodv4rNiJRchCzutFw5ItR_Z27CM)
- Deeplearning.ai Deep Learning Specialization
- NYU: Deep Learning
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Specializations
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Recommendation Systems
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Information Retrieval and Web Search
- Introduction to Information Retrieval
- Stanford CS224U: Natural Language Understanding - NLU and Information Retrieval
- TU Wein: Crash Course IR - Fundamentals
- UIUC: Text Retrieval and Search Engines
- Stanford CS276: Information Retrieval and Web Search
- University of Freiburg: Information Retrieval
- Stanford CS224U: Natural Language Understanding - NLU and Information Retrieval
- TU Wein: Crash Course IR - Fundamentals
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Natural Language Processing
- Introduction to Natural Language Processing
- Stanford CS224n: Natural Language Processing with Deep Learning
- NYU: DS-GA 1011 Natural Language Processing with Representation Learnin
- Deeplearning.ai Natural Language Processing Specialization - nlp-specialization)]
- Deeplearning.ai Natural Language Processing Specialization - nlp-specialization)]
- Speech and Language Processing
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Unsupervised Learning and Generative Models
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Reinforcement Learning
- Reinforcement Learning
- Coursera: Reinforcement Learning Specialization
- Stanford CS234: Reinforcement Learning
- Berkeley CS285: Deep Reinforcement Learning
- CS 330: Deep Multi-Task and Meta Learning
- Berekley: Deep Reinforcement Learning Bootcamp
- OpenAI Spinning Up
- Video 1 - FCNryj-GUn2a.21yA0Q1WPwhwZMgF?startTime=1610560965000) [Slides](https://drive.google.com/file/d/1KSFVptieJ-b115mLqAYfp2pVhJZ02qWh/view?usp=sharing)
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Robotics :robot:
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TL;DR
Programming Languages
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