Machine learning books and papers

Forecasting: Principles and Practice

📚 Book

@Machine_learn

Article Title:
Uncertainty Quantification for Language Models: A Suite of Black-Box, White-Box, LLM Judge, and Ensemble Scorers


PDF Download Link:
https://arxiv.org/pdf/2504.19254v2.pdf

GitHub:
• https://github.com/cvs-health/uqlm

Datasets:
• GSM8K
• SVAMP
• PopQA
@Machine_learn

Owen 3 release

📖 Blog


@LLM_learning

COUNTING THE NUMBER OF Zp-AND Fp[t]-FIXED POINTS OF A DISCRETE DYNAMICAL
SYSTEM WITH APPLICATIONS FROM ARITHMETIC STATISTICS

📚 Read


@Machine_learn

A Tutorial on Meta-Reinforcement
Learning

📚 Read

@Machine_learn

MuLoCo: Muon is a practical inner optimizer for DiLoCo

📚 Read

@Machine_learn

System Card: Claude Opus 4 & Claude Sonnet 4

📚 Book


@Machine_learn

TabSTAR: A Foundation Tabular Model With
Semantically Target-Aware Representations

📚 Paper

@Machine_learn

EgoDex: Learning Dexterous Manipulation from Large-Scale Egocentric Video

📚 Paper

@Machine_learn

THE WAY OF CODE The Timeless Art of Vibe Coding

📚 link


@Machine_learn

Paper2Code: Automating Code Generation from Scientific Papers in Machine Learning

24 Apr 2025 · Minju Seo, Jinheon Baek, Seongyun Lee, Sung Ju Hwang ·



Paper: https://arxiv.org/pdf/2504.17192v2.pdf

Code: https://github.com/going-doer/paper2code

@Machine_learn

🎓Advanced Applications of Machine Learning in Bioinformatics



🗓Publish year: 2025

📎 Study thesis


@Machine_learn

The 2025 AI Index Report

📚 Read

@Machine_learn

Reinforcement Learning: An Overview

📚 Book


@Machine_learn

Deliberation on Priors: Trustworthy Reasoning of Large Language Models on Knowledge Graphs

🖥 Github: https://github.com/reml-group/deliberation-on-priors

📕 Paper: https://arxiv.org/abs/2505.15210v1

@Machine_learn

Machine learning books and papers pinned Deleted message

Probability Cheatsheet
@Machine_learn

Full PyTorch Implementation of
Compressive Transformer

📚 Link


@Machine_learn

DeepSeek-Coder

DeepSeek Coder is composed of a series of code language models, each trained from scratch on 2T tokens, with a composition of 87% code and 13% natural language in both English and Chinese. We provide various sizes of the code model, ranging from 1B to 33B versions. Each model is pre-trained on project-level code corpus by employing a window size of 16K and an extra fill-in-the-blank task, to support project-level code completion and infilling. For coding capabilities, DeepSeek Coder achieves state-of-the-art performance among open-source code models on multiple programming languages and various benchmarks.

Creator: Deepseek-AI
Stars ⭐️: 15.6k
Forked by: 1.5k

Github Repo:
https://github.com/deepseek-ai/DeepSeek-Coder

@Machine_learn

Exercises in Machine Learning


Download, read, and practice:
arxiv.org/pdf/2206.13446

GitHub Repo: https://github.com/michaelgutmann/ml-pen-and-paper-exercises


@Machine_learn