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personal

Contains Jupiter Notebooks of stuff I am working on.

pipeline-docs

Some Pipeline.IO Usecase Documentation

polyaxon

A platform that helps you build, manage and monitor deep learning models

postgres-11-pg_similarity

pwc

Papers with code. Sorted by stars. Updated weekly.

pydata-berlin2017-pandas-and-dask-from-the-inside

pydata_berlin_2018

Slides and code for the PyData Berlin 2018 tutorial

pygam

[SEEKING FEEDBACK] Generalized Additive Models in Python

pymf

Python Matrix Factorization Module

python-machine-learning-book-2nd-edition

The "Python Machine Learning (2nd edition)" book code repository and info resource

pythondatasciencehandbook

Python Data Science Handbook: full text in Jupyter Notebooks

pytorch-semseg

Semantic Segmentation Architectures Implemented in PyTorch

pytorch-seq2seq

Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText. [IN PROGRESS]

pytorch-tutorial

PyTorch Tutorial for Deep Learning Researchers

pytorch_tutorial

PyTorch tutorial for PyData Berlin

resnetcam-keras

Keras implementation of a ResNet-CAM model

rivescript-python

A RiveScript interpreter for Python. RiveScript is a scripting language for chatterbots.

rl-quadcopter-2

Teach a Quadcopter How to Fly!

robo

RoBO: a Robust Bayesian Optimization framework

rstudioconf2018slides

Links to slides for talks at the rstudio::conf 2018

sagemaker-deployment

Code and associated files for the deploying ML models within AWS SageMaker

sagemaker-recommender-workshop

Amazon SageMaker Recommender Workshop

scikit-learn

scikit-learn: machine learning in Python

semantic-segmentation-suite

Semantic Segmentation Suite in TensorFlow. Implement, train, and test new Semantic Segmentation models easily!

serving

A flexible, high-performance serving system for machine learning models

setup.py

📦 A Human's Ultimate Guide to setup.py.

smac3

Sequential Model-based Algorithm Configuration

spearmint

Spearmint is a package to perform Bayesian optimization according to the algorithms outlined in the paper: Practical Bayesian Optimization of Machine Learning Algorithms. Jasper Snoek, Hugo Larochelle and Ryan P. Adams. Advances in Neural Information Processing Systems, 2012

spectral_clustering

stargan

PyTorch Implementation of StarGAN - CVPR 2018