<table> <tr><td> <a href="https://www.reddit.com/r/MachineLearning/comments/1wy99gd/i_have_trained_a_model_to_predict_my_blood_sugar/"> <img alt="I have trained a model to predict
<!-- SC_OFF --><div class="md"><p>Small MLP (2 layers × 256 units, ~85 KB) that accurately predicts 58 <a href="https://github.com/naver/anny">Anny</a> body-shape parameters from
<!-- SC_OFF --><div class="md"><p>Link to the paper:</p> <p><a
<!-- SC_OFF --><div class="md"><p>After burning way too much money on GPT-4 API calls, I finally went all-in on local models with Ollama. The progress in 2026 is insane
<!-- SC_OFF --><div class="md"><p>​</p> <p>## Abstract</p> <p>Post-training makes language models more decisive without necessarily making them more accurate — and we find
<!-- SC_OFF --><div class="md"><p>Until last week, generating an image inside Claude meant Claude wrote you a prompt. Then you copied it. Opened another tab. Pasted it into
<!-- SC_OFF --><div class="md"><p>Been a UFC fan for years and recently had some spare time to build a web app that uses Machine Learning to predict which fighter will win as a
<!-- SC_OFF --><div class="md"><p>Hey everyone,</p> <p>I’ve been building an end-to-end Air Quality (PM2.5) forecasting pipeline for 4 countries (US, UK, India, Australia) using
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