aramvillasana Goto Github PK

2012-01_stanford_cs228

Probabilistic Graphical Models

auxiliary-task-for-text-to-sql

beto

BETO - Spanish version of the BERT model

coarse2fine

coursera

Quiz & Assignment of Coursera

deep-learning-for-recommendation-systems

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

dlmai

RNN examples

emnlp2019-adjective-knowledge-for-text-to-sql

Source code for EMNLP2019 paper "Leveraging Adjective-Noun Phrasing Knowledge for Comparison Relation Prediction in Text-to-SQL".

hydranet-wikisql

Hybrid ranking network for text-to-SQL

imas-team8

agent-based decision support system (A-DSS). The system will process data about one particular domain. In this sense, all data will be picked up from a well-known repository as UCI Machine Learning

irnet

An algorithm for cross-domain NL2SQL

lang2logic

nl2sql

Bidirectional Attention for SQL Generation

nl2sql-rule

Content Enhanced BERT-based Text-to-SQL Generation

pointersql

Code for PointerSQL, PT-MAML, Execution-guided Decoding papers

question-generation-vae

The code for the EMNLP2018 paper "Question Generation from SQL Queries Improves Neural Semantic Parsing"

rat-sql

A relation-aware semantic parsing model from English to SQL

recsysmaster

MASTER IN FOUNDATIONS OF DATA SCIENCE: Recommender Systems

sqlnet

Neural Network for generating structured queries from natural language.

sqlova

sqlova-debug-read

pycharm debuggable cpu version for sqlova

syntaxsql

SyntaxSQLNet: Syntax Tree Networks for Complex and Cross Domain Text-to-SQL Task

syntaxsql-python3

Python3 and PyTorch1.1 and CPU-debug version for SyntaxSQLNet

syntaxsqlnet

Python 3 reimplementation of SyntaxSQLNet, including several improvements

syntaxsqlnet-1

SyntaxSQLNet - Python 3 & PyTorch 1.0

text2sql

treqs

Text-to-SQL Generation for Question Answering on Electronic Medical Records

typesql-python3

TypeSQL: Knowledge-based Type-Aware Neural Text-to-SQL Generation

upc-mai-dl.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

w2v_ol

Using word embeddings (word2vec) for ontology learning