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kaltura-live-android

Android app for Live Streaming using Kaltura

kaltura-media-framework-docker-compose

A docker compose for https://github.com/kaltura/media-framework

kanjian-music-api-doc

kanjian-music-php-sdk

kanon-android

ubc music android stuffs

kapre

kapre: Keras Audio Preprocessors

kaproxy

Restful HTTP Proxy For Kafka

karlo

kats

Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics, detecting change points and anomalies, to forecasting future trends.

kenburnsview

Android ImageViews animated by Ken Burns Effect

kendo-music-store

End-to-end Demo Application built with Kendo UI (based on the original Microsoft MVC Music Store Demo)

kepler.gl

Kepler.gl is a powerful open source geospatial analysis tool for large-scale data sets.

kepoj

KepoJ is a library that provides creating, using, training and exporting ml-agents and neural networks.

keras-bigan

BiGAN implementation in Keras to detect similarities in Landscapes.

key-list

keyhunt

privkey hunt for crypto currencies that use secp256k1 elliptic curve

keypoint_promptable_reidentification

[ECCV24] Keypoint Promptable Re-Identification: SOTA ReID method robust to occlusions and multi-person ambiguity

kkbox-music-recommendation

https://www.kaggle.com/c/kkbox-music-recommendation-challenge

kkbox-music-recommendation-system

Music Recommendation system is all about recommending the songs which the user like based on their previous activities like searches, previously listened songs, etc. There are many techniques for building a recommendation like Collaborative Filtering, Content Based filtering, Hybrid methods (Combining both Content Based and Collaborative Filtering methods). In this challenge we have to build a recommendation system that can predict whether a user will listen to a song again within one month after the user's very first observable listening event in KKBox application. If the user did not listen to the song again within one month, the target variable will be 0, and 1 otherwise.  Business Problem :This can helps KKBox company to recommend songs to users, to apply rating to songs, to determine the taste in songs of user. ML Formulation : Building a recommendation system using Collaborative based algorithms like matrix factorization and word embedding. Performance Metric : Performance metric for the challenge Area under Receiver Operating Characteristic Curve (AUC ROC) Score. As the both the classed are balanced in dataset so, we will choose AUC ROC not F1-Score. We can also choose Accuracy over AUC ROC as classes are balanced but advantage of AUC ROC score is that we can get correct threshold if we are using linear models like Linear Regression or Logistic Regression.

kkbox-s-music-recommendation-challenge-case-study

I build a model which can predict whether a user will re-listen to that song by evaluating given features of the user and songs.Our business objective is to recommend song which user already listen in past but user like to re-listen that song.

kkbox_music_recommendation

knet

Android network library with QUIC protocol supporting.

knightonline

OpenKO is an open source version of the old school Knight Online MMORPG

knn-graph

Building KNN Graph for Billion High Dimensional Vectors Efficiently

knowclip

Quickly make Anki flashcards from video and audio files, with handy features like silence detection and subtitles integration.

knowledgegraphdata

史上最大规模1.4亿中文知识图谱开源下载

koel

A personal music streaming server that works.

koel-player

Koel Player, the official mobile app for Koel.

kolors

Kolors Team

konekto

object-graph mapper for agensgraph