bvasil Goto Github PK

azurechatgpt

deep-learning-for-recommendation-systems

This repository contains Deep Learning based articles , paper and repositories for Recommender Systems

deeplearning

Deep Learning introduction and its application in various fields

evaluation-measures

Evaluation Measures for the BioASQ project

gsoc2018-3gm

💫 Automated codification of Greek Legislation with NLP

interprettensor

lexpredict-contraxsuite

LexPredict ContraxSuite

lexpredict-lexnlp

LexNLP by LexPredict

movies-recommender-system

This is a recommender system applied in two different approaches: 1) Simple model 2) Neural Network based model Both models outperform the academic benchmarks with few epochs of training, with the second gives state of the art like results. I use the famous Movielens mini dataset in this project, which has users' ratings of movies. The aim of the project is to showcase a simple recommender system which is able to predict which movies certain user would probably like most by looking at what similar users liked. I used keras library as the core backbone for this project.

muscle-spindle

neuroner

Named-entity recognition using neural networks. Easy-to-use and state-of-the-art results.

neyribazurechatgpt

ngcm-tutorial

Materials for the IPython/Jupyter workshop at the NGCM Summer Academy, at Southampton University, Boldrewood campus.

python-benedict

dict subclass with keylist/keypath support, normalized I/O operations (base64, csv, ini, json, pickle, plist, query-string, toml, xml, yaml) and many utilities. :blue_book:

qdrant-helm

scientific_programming

triplet_recommendations_keras

An example of doing MovieLens recommendations using triplet loss in Keras