MISeD (Meeting Information Seeking Dialogs dataset) is an information-seeking dialog dataset focused on meeting transcripts. It includes 432 dialogs over transcripts from the QMSum dataset. MISeD i…

List of articles related to deep learning applied to music

Stochastic Neighbor and Crowd Kernel (SNaCK) embeddings: Quick and dirty visualization of large-scale datasets via concept embeddings

DyNet: The Dynamic Neural Network Toolkit

A list of past meetups of the DataTalks meetup series and related resources.

pyclustering is a Python, C++ data mining library.

Magenta: Music and Art Generation with Machine Intelligence

doing audio digital signal processing in tensorflow to try to recreate digital audio effects

Neural network visualization toolkit for keras

From word2vec to chord2vec tensorFlow implementation

Long live PyCon Israel!

dna2vec: Consistent vector representations of variable-length k-mers

Pytorch implementation of "One-Sided Unsupervised Domain Mapping" NIPS 2017

Keras package for region-based convolutional neural networks (RCNNs)

CNTK based implementation of Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

Summaries of machine learning papers

Implementation of Super Resolution CNN in Keras.

An implementation of CycleGan using TensorFlow

Persistent, stale-free, local and cross-machine caching for Python functions.

Deep metric learning using Triplet network

The demo code for "Neural network-based clustering using pairwise constraints" (http://arxiv.org/abs/1511.06321)

A Python implementation of COP-KMEANS algorithm

The Retro Learning Environment (RLE) -- a learning framework for AI

Deep Embedding Clustering in Keras

Configure Caffe in one hour for Windows users.

YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet )

a yolo windows version(for object detection)

Extension of the public darknet repository with additional features and code improvements for YOLO.

A tutorial on the t-SNE learning algorithm