Brendan Fortuner's repositories
ml-glossary
Machine learning glossary
pyairtable
Python Api Client for Airtable
hardhat-basics
Playing with Solidity and Hardhat
pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
tensorflow
An Open Source Machine Learning Framework for Everyone
arrow
Apache Arrow is a cross-language development platform for in-memory data. It specifies a standardized language-independent columnar memory format for flat and hierarchical data, organized for efficient analytic operations on modern hardware. It also provides computational libraries and zero-copy streaming messaging and interprocess communication. Languages currently supported include C, C++, Java, JavaScript, Python, and Ruby.
petastorm
Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code.
keep-a-changelog
If you build software, keep a changelog.
openpifpaf
Official implementation of "PifPaf: Composite Fields for Human Pose Estimation" in PyTorch.
SpatialEmbeddings
Instance Segmentation by Jointly Optimizing Spatial Embeddings and Clustering Bandwidth
PIXOR
PyTorch Implementation of PIXOR
pytorch_tiramisu
FC-DenseNet in PyTorch for Semantic Segmentation
elasticsearch-dsl-py
High level Python client for Elasticsearch
computer-vision
Computer vision sabbatical study materials
machine-learning
Machine learning sabbatical study materials
computer-architecture
Intro to computer architecture
learning_data_aug
OpenAI Request for Research - https://blog.openai.com/requests-for-research-2/
catalyst
An Algorithmic Trading Library for Crypto-Assets in Python
Mask_RCNN
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
gdax-python
The unofficial Python client for the GDAX API
AndroidDemo
Quick prototyping app to learn Android basics
PyTorch2Android
Run PyTorch models on Android
AndroidCaffe2
Demo deploying PyTorch/Caffe2 models to Android