Weekly Machine Learning Opensource Roundup – Sep. 27, 2018

Examples

Coursera Machine Learning MOOC by Andrew Ng
Python assignments for the machine learning class by andrew ng on coursera with complete submission for grading capability and re-written instructions.

Just Enough Scala for Spark
A tutorial on the most important features and idioms of Scala that you need to use Spark’s Scala APIs.

Lit2Vec
Representing Books as vectors using the Word2Vec algorithm

deep learning object detection
A paper list of object detection using deep learning

Toolsets

Transfer Learning Suite
Transfer Learning Suite in Keras. Perform transfer learning using any built-in Keras image classification model easily!

jiant
jiant sentence representation learning toolkit is an extensible platform meant to make it easy to run experiments that involve multitask and transfer learning across sentence-level NLP tasks.

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

Models

generative-models
Annotated, understandable, and visually interpretable PyTorch implementations of: VAE, BIRVAE, NSGAN, MMGAN, WGAN, WGANGP, LSGAN, DRAGAN, BEGAN, RaGAN, InfoGAN, fGAN, FisherGAN

Optical Flow Prediction with TensorFlow
Implements “PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume,” by Deqing Sun et al. (CVPR 2018)

PyTorch Image Dehazing
PyTorch implementation of some single image dehazing networks.

Libraries

mia
A library for running membership inference attacks (MIA) against machine learning models

apricot
apricot implements submodular selection for the purpose of selecting subsets of massive data sets to train machine learning models quickly.

 

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