Hacker News
- LightGBM – A fast, distributed, gradient boosting framework https://github.com/Microsoft/LightGBM 11 comments
Linking pages
- Leaving Apple Inc. | Max Woolf's Blog http://minimaxir.com/2017/05/leaving-apple/ 93 comments
- GitHub - josephmisiti/awesome-machine-learning: A curated list of awesome Machine Learning frameworks, libraries and software. https://github.com/josephmisiti/awesome-machine-learning 58 comments
- GitHub - lemire/fast_double_parser: Fast function to parse strings into double (binary64) floating-point values, enforces the RFC 7159 (JSON standard) grammar: 4x faster than strtod https://github.com/lemire/fast_double_parser 56 comments
- Lookism in TikTok. Intro | by Enryu | Sep, 2022 | Medium https://medium.com/@enryu9000/lookism-in-tiktok-3def0f20cf78 31 comments
- GitHub - fastfloat/fast_float: Fast and exact implementation of the C++ from_chars functions for float and double types: 4x to 10x faster than strtod, part of GCC 12 and WebKit/Safari https://github.com/fastfloat/fast_float 17 comments
- 10 Machine Learning Methods that Every Data Scientist Should Know | by Jorge Castañón | Towards Data Science https://medium.com/p/10-machine-learning-methods-that-every-data-scientist-should-know-3cc96e0eeee9 14 comments
- GitHub - zziz/pwc: This repository is no longer maintained. https://github.com/zziz/pwc 13 comments
- Ruby ML for Python Coders https://ankane.org/ruby-ml-for-python-coders 11 comments
- Elo Ratings v. Machine Learning: Predicting Chess Game Results | Pawnalyze https://pawnalyze.com/tournament/2022/02/27/Elo-Rating-Accuracy-Is-Machine-Learning-Better.html 11 comments
- GitHub - microsoft/hummingbird: Hummingbird compiles trained ML models into tensor computation for faster inference. https://github.com/microsoft/hummingbird/ 10 comments
- 10 Machine Learning Methods that Every Data Scientist Should Know | by Jorge Castañón | Towards Data Science https://towardsdatascience.com/10-machine-learning-methods-that-every-data-scientist-should-know-3cc96e0eeee9 9 comments
- Building a Better Search Engine for Semantic Scholar | by Sergey Feldman | AI2 Blog https://medium.com/ai2-blog/building-a-better-search-engine-for-semantic-scholar-ea23a0b661e7 8 comments
- GitHub - fabsig/GPBoost: Combining tree-boosting with Gaussian process and mixed effects models https://github.com/fabsig/GPBoost 5 comments
- GitHub - tensorchord/Awesome-LLMOps: An awesome & curated list of best LLMOps tools for developers https://github.com/tensorchord/Awesome-LLMOps 5 comments
- GitHub - xplainable/xplainable: Real-time explainable machine learning for business optimisation https://github.com/xplainable/xplainable 4 comments
- GitHub - rmitsuboshi/miniboosts: A collection of boosting algorithms written in Rust 🦀 https://github.com/rmitsuboshi/miniboosts 3 comments
- GitHub - Xtra-Computing/thundergbm: ThunderGBM: Fast GBDTs and Random Forests on GPUs https://github.com/Xtra-Computing/thundergbm 2 comments
- GitHub - microsoft/DMTK: Microsoft Distributed Machine Learning Toolkit https://github.com/Microsoft/DMTK 1 comment
- GitHub - NannyML/nannyml: Detecting silent model failure. NannyML estimates performance for regression and classification models using tabular data. It alerts you when and why it changed. It is the only open-source library capable of fully capturing the impact of data drift on performance. https://github.com/NannyML/nannyml 1 comment
- Top 50 Important Python Libraries! https://blog.octachart.com/top-50-important-python-libraries 1 comment
Linked pages
- GitHub - dotnet/machinelearning: ML.NET is an open source and cross-platform machine learning framework for .NET. https://github.com/dotnet/machinelearning 76 comments
- GitHub - BayesWitnesses/m2cgen: Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies https://github.com/bayeswitnesses/m2cgen 33 comments
- GitHub - slundberg/shap: A game theoretic approach to explain the output of any machine learning model. https://github.com/slundberg/shap 20 comments
- GitHub - postgresml/postgresml: PostgresML is an end-to-end machine learning system. It enables you to train models and make online predictions using only SQL, without your data ever leaving your favorite database. https://github.com/postgresml/postgresml 15 comments
- GitHub - microsoft/hummingbird: Hummingbird compiles trained ML models into tensor computation for faster inference. https://github.com/microsoft/hummingbird/ 10 comments
- GitHub - MAIF/shapash: 🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models https://github.com/MAIF/shapash 2 comments
- GitHub - microsoft/SynapseML: Simple and Distributed Machine Learning https://github.com/microsoft/SynapseML 0 comments
- GitHub - parrt/dtreeviz: A python library for decision tree visualization and model interpretation. https://github.com/parrt/dtreeviz 0 comments
- GitHub - microsoft/FLAML: A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP. https://github.com/microsoft/FLAML 0 comments
- GitHub - mlflow/mlflow: Open source platform for the machine learning lifecycle https://github.com/mlflow/mlflow/ 0 comments
- GitHub - mars-project/mars: Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions. https://github.com/mars-project/mars 0 comments
- GitHub - siboehm/lleaves: Compiler for LightGBM gradient-boosted trees, based on LLVM. Speeds up prediction by ≥10x. https://github.com/siboehm/lleaves 0 comments