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kaggle-2014-criteo

kaggle-acquire-valued-shoppers-challenge

Kaggle code for Acquire Valued Shoppers Challenge

kaggle-acquire-valued-shoppers-challenge-1

Kaggle: Shoppers

kaggle-airbnb

:earth_africa: Where will a new guest book their first travel experience?

kaggle-avito

https://www.kaggle.com/c/avito-context-ad-clicks/forums

kaggle-criteo

Code for Criteo competition http://www.kaggle.com/c/criteo-display-ad-challenge

kaggle-quora-question-pairs-4th

Kaggle：Quora Question Pairs, 4th/3396 (https://www.kaggle.com/c/quora-question-pairs)

kaggle-web-traffic

1st place solution

kaggle_acquire-valued-shoppers-challenge

Code for the Kaggle acquire valued shoppers challenge

kartograph.py

Renders beautiful SVG maps in Python.

kclist

Algorithms to list k-cliques in real-world graphs

keras

Deep Learning library for Python. Runs on TensorFlow, Theano, or CNTK.

keras-adamw

Keras implementation of AdamW, SGDW, NadamW, Warm Restarts, and Learning Rate multipliers

keras-bert

Implementation of BERT that could load official pre-trained models for feature extraction and prediction

keras-glove

Implementation of GloVe in Keras

keras-quora-question-pairs

A Keras model that addresses the Quora Question Pairs dyadic prediction task.

keras-recommendation

Using Keras to implement recommender systems

keras-rl

Deep Reinforcement Learning for Keras.

keras-tensorflow-yolov2

YAD2K: Yet Another Darknet 2 Keras

keras-wide-n-deep

Reimplementation of Google's Wide & Deep Network in Keras

keras-yolo3

A Keras implementation of YOLOv3 (Tensorflow backend)

kmcuda

Large scale K-means and K-nn implementation on NVIDIA GPU / CUDA

knn4qa

k-nearest neighbor search for question answering (QA) and information retrieval (IR)

knowledge-enhanced-recommendation

kotlinx-lincheck

Framework for testing concurrent data structures for correctness

ksql

KSQL - a Streaming SQL Engine for Apache Kafka

ktext

Utilities for preprocessing text for deep learning with Keras

l4-optimizer

Code for paper "L4: Practical loss-based stepsize adaptation for deep learning"

lambda-opt

Pytorch implementation of λOpt: Learn to Regularize Recommender Models in Finer Levels, KDD 2019

lambdafm

Multi-thread implementation of lambdaFM with FTRL for ranking problem. LambdaFM is a learning-to-rank algorithm by combining LambdaRank and Factorization Machines.