Weekly Machine Learning Opensource Roundup – Apr. 18, 2019

Examples

Feature Transfer App
Image editing for people bad at photoshop

SpaCy Course
Advanced NLP with spaCy: A free online course

Awesome Mobile Machine Learning
A curated list of awesome mobile machine learning resources for iOS, Android, and edge devices

Deep Learning NN from scratch
This repository has modules which will simulate a 3-layer NN. The modules are built from scratch without using any GPU framework library. Simulations include forward and backward propagation for every node of sigmoid/softmax activiation.

neural networks from scratch
An implementation of convolutional networks in NumPy!

epsilon Explore
ε-Explore is a novel approach to training a chess engine using supervised learning on a single GPU and CPU.

The Apriori Algorithm for Unsupervised Learning in R
investigation of retail transaction data from a country store in the Catskills

Toolsets

SMAC
SMAC is WhiRL’s environment for research in the field of collaborative multi-agent reinforcement learning (MARL) based on Blizzard’s StarCraft II RTS game

BentoML
Machine Learning Toolkit for packaging and deploying models

GanSeg
Framework for medical image segmentation using deep neural networks

dm2gym
Convert DeepMind Control Suite to OpenAI gym environments.

Models

SPADE
Semantic Image Synthesis with Spatially-Adaptive Normalization.

MorphNet
Fast & Simple Resource-Constrained Learning of Deep Network Structure

yolov3-tf2
YoloV3 Implemented in Tensorflow 2.0

RandWireNN
Implementing Randomly Wired Neural Networks for Image Recognition, Using CIFAR-10 dataset, CIFAR-100 dataset

bottom-up-attention-tf
Tensorflow implementation of “Bottom-up and Top-down attention for VQA”

RL-RND
Full Chainer implementation of OpenAI’s Reinforcement Learning using Random Network Distillation

CenterNet
Object detection, 3D detection, and pose estimation using center point detection:

Libraries

ttb
Tensor Toolbox for Modern Fortran

BlingFire
A lightning fast Finite State machine and REgular expression manipulation library. It is used for many linguistic operations inside Bing such as Tokenization, Multi-word expression matching, Unknown word-guessing, Stemming / Lemmatization just to mention a few.

Framework

Peloton
Unified Resource Scheduler to co-schedule mixed types of workloads such as batch, stateless and stateful jobs in a single cluster for better resource utilization.

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