List of papers recommended by a Pinterest employee: https://www.teamblind.com/article/ML-design-interview-3cYD0vdM
- Convex Optimization (Boyd)
- Introduction to Information Retrieval (Manning)
- Elements of Statistical Learning
- Introduction to Statistical Learning
- Foundations of Machine Learning (Mohri)
- Machine Learning Yearning by Andrew Ng (https://d2wvfoqc9gyqzf.cloudfront.net/content/uploads/2018/09/Ng-MLY01-13.pdf )
- Smola ( https://alex.smola.org/drafts/thebook.pdf )
- Airbnb ( https://medium.com/airbnb-engineering/tagged/machine-learning )
- Amazon?
- Deepmind ( https://deepmind.com/blog )
- Facebook ( https://ai.facebook.com/blog/ )
- Google ( https://cloud.google.com/blog/products/ai-machine-learning, https://ai.googleblog.com/, https://www.blog.google/technology/ai/,
- Linkedin (https://engineering.linkedin.com/blog/topic/machine-learning)
- Netflix ( https://research.netflix.com/research-area/machine-learning )
- Pinterest ( https://medium.com/pinterest-engineering/machine-learning/home, https://labs.pinterest.com/projects/machine-learning/ )
- Quora (https://www.quora.com/q/quoraengineering/Machine-Learning-at-Quora)
- Stripe ? ( https://stripe.com/blog/engineering/ ),
- Twitter ( https://blog.twitter.com/engineering/en_us/topics/insights.html )
- Uber ( https://eng.uber.com/research/?_sft_category=research-ai-ml )
- Andrew Ng's original coursera course
- Andrew Ng's deep learning courses
- Bloomberg ML course
- Fast.ai
- https://developers.google.com/machine-learning/guides/rules-of-ml/
- Kaggle.com
- Matrix and Gaussian Identity notes: https://cs.nyu.edu/~roweis/notes.html
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Software Engineering for ML (https://www.microsoft.com/en-us/research/uploads/prod/2019/03/amershi-icse-2019_Software_Engineering_for_Machine_Learning.pdf)
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Hidden Technical Debt in ML systems ( https://papers.nips.cc/paper/5656-hidden-technical-debt-in-machine-learning-systems.pdf )
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KDD
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NIPS, I linked a single paper but it's a great source in general ( https://papers.nips.cc/paper/7595-probabilistic-matrix-factorization-for-automated-machine-learning.pdf )
- Yoshua Bengio
- Fei-Fei Li
- Trevor Hastie
- Jiawei Han
- Surya Ganguli
- Michael Jordan
- Guy Lebanon
- Yann LeCun
- Geoffrey Hinton
- Gary Marcus
- Andrew Ng
- Robert Tibshirani
- Ashutosh Saxena
- Alex Smola
- Cracking the ML Design Interview:
- E-commerce, design a system that determines which site visitors should be sent a discount code.
- Design a system for ranking the search results (Linkedin jobs, amazon shopping, etc)