feay1234

CARA

An implementation of Contextual Attention Recurrent Architecture (SIGIR 2018)

ASASRec

Sequential-based Adversarial Optimisation for Personalised Top-N Item Recommendation

CrossBERT

CrossBERT: a Triplet Neural Architecture for Ranking EntityProperties

RSC2019

RecSys Challenge 2019 Deep Learning Models

TLF-SDA

RNNBPR

2019

Adversarial-Collaborative-Filtering

CRCF

An implementation of Contextual Recurrent Collaborative Filtering Framework (Information Processing and Management Journal 2019)

alexa-with-dstc9-track1-dataset

DSTC9 Track 1 - Beyond Domain APIs: Task-oriented Conversational Modeling with Unstructured Knowledge Access

anomaly-detection-datasets

Real-world anomaly detection datasets

Deep-SAD-PyTorch

A PyTorch implementation of Deep SAD, a deep Semi-supervised Anomaly Detection method.

Dialog-System-Technology-Challenge

Dialog System Technology Challenge

dialoglue

DialoGLUE: A Natural Language Understanding Benchmark for Task-Oriented Dialogue

keras

Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on Theano or TensorFlow.

Keras-GAN

Keras implementations of Generative Adversarial Networks.

keras-recommendation

Using Keras to implement recommender systems

keras_snli

Simple Keras model that tackles the Stanford Natural Language Inference (SNLI) corpus using summation and/or recurrent neural networks

librec

LibRec: A Java Library for Recommender Systems, see

machine-learning-systems-design

A booklet on machine learning systems design with exercises

ocr_tflite

This repository is to create tflite models for the available ocr models

RecSys2017

diagrams

SM-DST

som-dst

SOM-DST: Efficient Dialogue State Tracking by Selectively Overwriting Memory (ACL 2020)

Tabular-data-Winning-Solution

Rank gaussian normalization, Swap noise, Denoised AutoEncoder as feature engineering

test

TFIDF-Word-Representation

transformers

🤗 Transformers: State-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch.

triplet_recommendations_keras

An example of doing MovieLens recommendations using triplet loss in Keras

WikiHow-Task-Based