Hacker News
- A visual proof that neural nets can compute any function http://neuralnetworksanddeeplearning.com/chap4.html 189 comments
- A visual proof that neural nets can approximate any function http://neuralnetworksanddeeplearning.com/chap4.html 128 comments
- A visual proof that neural nets can compute any function http://neuralnetworksanddeeplearning.com/chap4.html 65 comments
- A visual proof that neural nets can compute any function http://neuralnetworksanddeeplearning.com/chap4.html 80 comments
- A visual proof that neural nets can compute any function (universal approximation theorem) http://neuralnetworksanddeeplearning.com/chap4.html 18 comments compsci
- A visual proof that neural nets can compute any function. [Chapter 4 of Nielsen's 'Neural Networks and Deep Learning'] http://neuralnetworksanddeeplearning.com/chap4.html 11 comments compsci
- A visual proof that neural nets can compute any function http://neuralnetworksanddeeplearning.com/chap4.html 29 comments math
Linking pages
- What makes Math mysterious — some brilliant results in Math | by Konark Jain | Medium https://medium.com/@konark145/what-makes-math-mysterious-some-brilliant-results-in-math-de9b02cd7d6c 4 comments
- GitHub - guillaume-chevalier/Awesome-Deep-Learning-Resources: Rough list of my favorite deep learning resources, useful for revisiting topics or for reference. I have got through all of the content listed there, carefully. - Guillaume Chevalier https://github.com/guillaume-chevalier/awesome-deep-learning-resources 1 comment
- Understanding building blocks of ULMFIT | by Kerem Turgutlu | ML Review https://medium.com/@keremturgutlu/understanding-building-blocks-of-ulmfit-818d3775325b 1 comment
- Rohan & Lenny #3: Recurrent Neural Networks & LSTMs | by Rohan Kapur | A Year of Artificial Intelligence https://ayearofai.com/rohan-lenny-3-recurrent-neural-networks-10300100899b 0 comments
- Deep Learning is Accessible. You’re curious about deep learning but… | by Andrew Lin | Building VTS https://buildingvts.com/deep-learning-is-accessible-30c11792af8b 0 comments
- Convolutional neural networks for artistic style transfer — Harish Narayanan https://harishnarayanan.org/writing/artistic-style-transfer/ 0 comments
- Visual Networks: The Marketing Consultant | by Italo Sayan | Towards Data Science https://towardsdatascience.com/visual-networks-the-marketing-consultant-d152b04a5e46 0 comments
- Faster AI: Lesson 2 — TL;DR version of Fast.ai Part 1 | by Kshitiz Rimal | Deep Learning Journal | Medium https://medium.com/deep-learning-journals/faster-ai-lesson-2-tl-dr-version-of-fast-ai-part-1-f803218ffe6d 0 comments
- GitHub - guillaume-chevalier/Awesome-Deep-Learning-Resources: Rough list of my favorite deep learning resources, useful for revisiting topics or for reference. I have got through all of the content listed there, carefully. - Guillaume Chevalier https://github.com/guillaume-chevalier/favorite-deep-learning-papers 0 comments
- Deep Feelings about Deep Learning | by Carlos Argueta | Medium https://medium.com/@kidargueta/deep-feelings-about-deep-learning-8e300cdcc047#.1jpeplmny 0 comments
- Schedule | EECS 498-007 / 598-005: Deep Learning for Computer Vision https://web.eecs.umich.edu/~justincj/teaching/eecs498/WI2022/schedule.html 0 comments
- Intelligence as efficient model building | Alex’s blog https://atelfo.github.io/2023/05/17/intelligence-as-efficient-model-building.html 0 comments
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