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Nonagon Data
- Madrid, Spain
Stars
A modern (as of 2024) Flask API back end.
🔮 A refreshing functional take on deep learning, compatible with your favorite libraries
🎩 Dark & Light Accented Alfred Themes tailored for macOS Mojave & Catalina users.
surround.vim: Delete/change/add parentheses/quotes/XML-tags/much more with ease
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
A collection of various deep learning architectures, models, and tips
Collection of less popular features and tricks for the Python programming language
A collection of design patterns/idioms in Python
Lab materials for the Full Stack Deep Learning Course
Show, Attend, and Tell | a PyTorch Tutorial to Image Captioning
SSD: Single Shot MultiBox Detector | a PyTorch Tutorial to Object Detection
Little tools to download and then weed through images, delete and classify them into groups for building deep learning image datasets (based on crawler and tkinter)
Trained model files for dlib example programs.
The Places365-CNNs for Scene Classification
Largest multi-label image database; ResNet-101 model; 80.73% top-1 acc on ImageNet
Unofficial pytorch implementation for Self-critical Sequence Training for Image Captioning. and others.
🚀⭐ Minimalistic, powerful and extremely customizable Zsh prompt
A fast, efficient universal vector embedding utility package.
Image augmentation for machine learning experiments.
a small, expressive orm -- supports postgresql, mysql, sqlite and cockroachdb
Python stemming library using snowball stemmers
Simple image retrival on deep-fashion dataset with pytorch - A course project
A Web UI for Elasticsearch and OpenSearch: Import, browse and edit data with rich filters and query views, create reference search UIs.
Implementation of research papers on Deep Learning NLP CV in Python using Keras, Tensorflow and Scikit Learn.
A curated list of the most important and useful resources about elasticsearch: articles, videos, blogs, tips and tricks, use cases. All about Elasticsearch!
Lime: Explaining the predictions of any machine learning classifier