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Show HN: Intro to Machine Learning in Interactive D3.js Visualizations (r2d3.us) |
| recommended by 2 users | 2015 | 128 points by tonyhschu | original thread | |
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| 2. |
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“Mike Jordan at Berkeley sent me his list on what people should learn for ML.” (comment) |
| recommended by 2 users | 2010 | justokay on: Learning About Statistical Learning | original thread | |
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| 3. |
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Machine Learning 101 slidedeck: 2 years of headbanging, so you don't have to (docs.google.com) |
| recommended by 2 users | 2017 | 1656 points by flor1s | original thread | |
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| 4. |
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Ask HN: Best way to get started with AI? |
| recommended by 2 users | 2017 | 709 points by hackathonguy | original thread | |
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| 5. |
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Best Practices for ML Engineering from Google [pdf] (martin.zinkevich.org) |
| recommended by 2 users | 2017 | 406 points by tim_sw | original thread | |
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| 6. |
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A 'Brief' History of Neural Nets and Deep Learning (andreykurenkov.com) |
| recommended by 2 users | 2016 | 245 points by andreyk | original thread | |
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| 7. |
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Machine learning for financial prediction (robotwealth.com) |
| recommended by 2 users | 2016 | 214 points by Matetricks | original thread | |
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| 8. |
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The Simple Essence of Automatic Differentiation [pdf] (conal.net) |
| recommended by 2 users | 2018 | 167 points by bmc7505 | original thread | |
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| 9. |
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Show HN: A radically more scalable alternative to Bayesian Optimization (github.com) |
| recommended by 2 users | 2018 | 96 points by chroem- | original thread | |
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| 10. |
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Ask HN: How to get started with machine learning? |
| recommended by 1 user | 2016 | 950 points by georgehdd | original thread | |
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| 11. |
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The Unreasonable Effectiveness of Recurrent Neural Networks (karpathy.github.io) |
| recommended by 1 user | 2015 | 913 points by benfrederickson | original thread | |
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| 12. |
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The State of Machine Learning Frameworks (thegradient.pub) |
| recommended by 1 user | 2019 | 752 points by hughzhang | original thread | |
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| 13. |
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You could have invented transformers from memory (alexwang.ai) |
| recommended by 1 user | 2026 | 670 points by speckx | original thread | |
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| 14. |
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Every Model Learned by Gradient Descent Is Approximately a Kernel Machine (arxiv.org) |
| recommended by 1 user | 2020 | 406 points by scottlocklin | original thread | |
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| 15. |
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A Differentiable Programming System to Bridge ML and Scientific Computing (arxiv.org) |
| recommended by 1 user | 2019 | 381 points by ChrisRackauckas | original thread | |
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| 16. |
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SpaCy: Industrial-strength NLP with Python and Cython (honnibal.github.io) |
| recommended by 1 user | 2015 | 279 points by syllogism | original thread | |
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| 17. |
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Attention Is All You Need (papers.nips.cc) |
| recommended by 1 user | 2017 | 225 points by espeed | original thread | |
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| 18. |
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Learning About Statistical Learning (measuringmeasures.blogspot.com) |
| recommended by 1 user | 2010 | 208 points by liebke | original thread | |
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| 19. |
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Rest in Peas: The Unrecognized Death of Speech Recognition (robertfortner.posterous.com) |
| recommended by 1 user | 2010 | 138 points by robertfortner | original thread | |
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| 20. |
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Machine learning systems are stuck in a rut (blog.acolyer.org) |
| recommended by 1 user | 2019 | 133 points by feross | original thread | |
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| 21. |
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Large Scale Visual Recognition Challenge 2011 - Results (vision.stanford.edu) |
| recommended by 1 user | 2012 | 63 points by is74 | original thread | |
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| 22. |
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Goodbye, Data Science (ryxcommar.com) |
| recommended by 1 user | 2022 | 1 point by sonabinu | original thread | |
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| 23. |
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“The Illustrated Transformer is fantastic, but I would suggest that those going into it really should” (comment) |
| recommended by 1 user | 2023 | driscoll42 on: Transformers from Scratch | original thread | |
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