From f7b51a62078b6dfe8294de31670e891a5c350272 Mon Sep 17 00:00:00 2001 From: Vinta Chen Date: Sun, 22 Mar 2026 01:48:36 +0800 Subject: [PATCH] fix: update entries to use GitHub URLs as primary links spark.ml, django.db.models, and geodjango were pointing to documentation pages as their primary link rather than the GitHub repository. Move docs URLs inline as descriptive links so the primary link follows the standard GitHub-first convention. Co-Authored-By: Claude --- README.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index c5b2c8db..5812014a 100644 --- a/README.md +++ b/README.md @@ -160,7 +160,7 @@ _Libraries for Machine Learning. Also see [awesome-machine-learning](https://git - [mindsdb](https://github.com/mindsdb/mindsdb) - MindsDB is an open source AI layer for existing databases that allows you to effortlessly develop, train and deploy state-of-the-art machine learning models using standard queries. - [pgmpy](https://github.com/pgmpy/pgmpy) - A Python library for probabilistic graphical models and Bayesian networks. - [scikit-learn](https://github.com/scikit-learn/scikit-learn) - The most popular Python library for Machine Learning with extensive documentation and community support. -- [spark.ml](http://spark.apache.org/docs/latest/ml-guide.html) - [Apache Spark](http://spark.apache.org/)'s scalable Machine Learning library for distributed computing. +- [spark.ml](https://github.com/apache/spark) - [Apache Spark](https://spark.apache.org/)'s scalable [Machine Learning library](https://spark.apache.org/docs/latest/ml-guide.html) for distributed computing. - [xgboost](https://github.com/dmlc/xgboost) - A scalable, portable, and distributed gradient boosting library. ## Natural Language Processing @@ -360,7 +360,7 @@ _Libraries for sending and parsing email, and mail server management._ _Libraries that implement Object-Relational Mapping or data mapping techniques._ - Relational Databases - - [django.db.models](https://docs.djangoproject.com/en/dev/topics/db/models/) - The Django ORM. + - [django.db.models](https://github.com/django/django) - The Django [ORM](https://docs.djangoproject.com/en/dev/topics/db/models/). - [sqlalchemy](https://github.com/sqlalchemy/sqlalchemy) - The Python SQL Toolkit and Object Relational Mapper. - [awesome-sqlalchemy](https://github.com/dahlia/awesome-sqlalchemy) - [dataset](https://github.com/pudo/dataset) - Store Python dicts in a database - works with SQLite, MySQL, and PostgreSQL. @@ -487,7 +487,7 @@ _Libraries for visualizing data. Also see [awesome-javascript](https://github.co _Libraries for geocoding addresses and working with latitudes and longitudes._ - [django-countries](https://github.com/SmileyChris/django-countries) - A Django app that provides a country field for models and forms. -- [geodjango](https://docs.djangoproject.com/en/dev/ref/contrib/gis/) - A world-class geographic web framework. +- [geodjango](https://github.com/django/django) - A world-class geographic web framework that is part of [Django](https://docs.djangoproject.com/en/dev/ref/contrib/gis/). - [geojson](https://github.com/jazzband/geojson) - Python bindings and utilities for GeoJSON. - [geopandas](https://github.com/geopandas/geopandas) - Python tools for geographic data (GeoSeries/GeoDataFrame) built on pandas. - [geopy](https://github.com/geopy/geopy) - Python Geocoding Toolbox.