- [Meta] I wrote a bot for /r/learnprogramming that detects frequently asked questions and replies with helpful links https://en.wikipedia.org/wiki/Support_vector_machine 55 comments learnprogramming
Linking pages
- Introducing: Flickr PARK or BIRD | code.flickr.com http://code.flickr.net/2014/10/20/introducing-flickr-park-or-bird/ 522 comments
- Why the deep learning boom caught almost everyone by surprise https://www.understandingai.org/p/why-the-deep-learning-boom-caught 187 comments
- Machine Learning is Fun! Part 4: Modern Face Recognition with Deep Learning | by Adam Geitgey | Medium https://medium.com/@ageitgey/machine-learning-is-fun-part-4-modern-face-recognition-with-deep-learning-c3cffc121d78 112 comments
- How Should We Critique Research? · Gwern.net https://www.gwern.net/Research-criticism 81 comments
- How a stubborn computer scientist accidentally launched the deep learning boom - Ars Technica https://arstechnica.com/ai/2024/11/how-a-stubborn-computer-scientist-accidentally-launched-the-deep-learning-boom/ 36 comments
- Large-Scale Vehicle Classification – Pickled ML https://blog.aqnichol.com/2022/12/31/large-scale-vehicle-classification/ 25 comments
- Introduction to one-class Support Vector Machines - Roemer's blog http://rvlasveld.github.io/blog/2013/07/12/introduction-to-one-class-support-vector-machines/ 18 comments
- Machine Learning is Fun!. The world’s easiest introduction to… | by Adam Geitgey | Medium https://medium.com/@ageitgey/machine-learning-is-fun-80ea3ec3c471 17 comments
- Vectors From Leibniz to Einstein | https://mathenchant.wordpress.com/2023/12/17/vectors-from-leibniz-to-einstein/ 14 comments
- How 2400 sensors and machine learning models keep Sydney Harbour Bridge spanning the decades | Computerworld https://www.computerworld.com.au/article/648145/how-2400-sensors-machine-learning-models-keep-sydney-harbour-bridge-spanning-decades/ 13 comments
- Detect and Blur Faces Programmatically - DZone https://dzone.com/articles/detect-and-blur-faces-programmatically 9 comments
- Cheat Sheets for AI, Neural Networks, Machine Learning, Deep Learning & Big Data | by Stefan Kojouharov | Becoming Human: Artificial Intelligence Magazine https://becominghuman.ai/cheat-sheets-for-ai-neural-networks-machine-learning-deep-learning-big-data-678c51b4b463 9 comments
- Data Science: A Kaggle Walkthrough – Creating a Model – Brett Romero http://brettromero.com/wordpress/data-science-kaggle-walkthrough-creating-model/ 8 comments
- The Method to the Madness: Setting up a Python Workflow for Machine Learning — Steemit https://steemit.com/steemstem/@chosunone/the-method-to-the-madness-setting-up-a-python-workflow-for-machine-learning 7 comments
- The Believers https://chronicle.com/article/article-content/190147/ 6 comments
- Gaussian Processes are Not So Fancy https://planspace.org/20181226-gaussian_processes_are_not_so_fancy/ 6 comments
- The Believers http://chronicle.com/article/The-Believers/190147/ 4 comments
- Central Planning As Overfitting - RadicalxChange https://radicalxchange.org/blog/posts/2018-11-26-4m9b8b/ 3 comments
- Performance Comparison of Multi-Class Classification Algorithms | by Gursev Pirge | Medium https://gursev-pirge.medium.com/performance-comparison-of-multi-class-classification-algorithms-606e8ba4e0ee 2 comments
- Predicting Yelp Stars from Reviews with scikit-learn and Python http://www.developintelligence.com/blog/2017/03/predicting-yelp-star-ratings-review-text-python/ 1 comment
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