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 dustintran.com
On asymptotic convergence of averaged SGD | Dustin Tran
| | bdtechtalks.com
A simple guide to gradient descent in machine learning - TechTalks
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| | Gradient descent is the main technique for training machine learning and deep learning models. Read all about it.
| | fa.bianp.net
On the Convergence of the Unadjusted Langevin Algorithm
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| | The Langevin algorithm is a simple and powerful method to sample from a probability distribution. It's a key ingredient of some machine learning methods such as diffusion models and differentially private learning. In this post, I'll derive a simple convergence analysis of this method in the special case when the ...
| | michael-lewis.com
A machine learning glossary for hackers ยท Michael I Lewis
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| | This is a short summary of some of the terminology used in machine learning, with an emphasis on neural networks. I've put it together primarily to help my own understanding, phrasing it largely in non-mathematical terms. As such it may be of use to others who come from more of a programming than a mathematical background.
| | thecodebarbarian.com
Building a Wine Tasting Neural Network with Node.js | www.thecodebarbarian.com
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| [AI summary] The article discusses building a neural network using Brain.js to predict wine quality ratings based on chemical properties, including data preprocessing, training, and evaluation.