[AI6122] Text Data Management & Processing

Overview

[AI6122] Text Data Management & Processing

====== I M P O R T A N T ======

The content in this repository should exclusively be utilized in sharing solutions for projects, communicating ideas for related problems, and references to similar assignments. If you are a student facing an assignment with the same or similar topics, you can use this repository as a reference, while the final report should include the citations of the repository. If you submit an assignment without proper acknowledgment after referring to this repository, you may be considered PLAGIARISM by your instructor, and the author will not pay ANY responsibility for this. Please refer to your teacher's and your school's instructions for the determination of academic integrity.

Moreover, if you are taking the AI6122 course, do not be stupid. You can utilize the materials here as a reference to construct your own assignment and reflect the citation to this repository in the final report. If you copy the code without citing it, you have violated NTU's academic integrity and are involved in plagiarism.

Please refer to the following links for NTU's determination of academic integrity and plagiarism:

https://ts.ntu.edu.sg/sites/intranet/dept/tlpd/ai/Pages/NTU-Academic-Integrity-Policy.aspx

https://ts.ntu.edu.sg/sites/intranet/dept/tlpd/ai/Pages/default.aspx

https://ts.ntu.edu.sg/sites/policyportal/new/Documents/All%20including%20NIE%20staff%20and%20students/Student%20Academic%20Integrity%20Policy.pdf

If you think the professor is easy to fool, think again.
You know who you are.

====== D I S C L A I M E R ======

This repository should only be used for reasonable academic discussions. I, the owner of this repository, never and will never ALLOWING another student to copy this assignment as their own. In such circumstances, I do not violate NTU's statement on academic integrity as of the time this repository is open (18/01/2022). I am not responsible for any future plagiarism using the content of this repository.



====== I N T R O D U C T I O N ======

[AI6122] Text Data Management & Processing is an elective course of Master of Science in Artificial Intelligence Graduate Programme (MSAI), School of Computer Science and Engineering (SCSE), Nanyang Technological University (NTU), Singapore. The repository corresponds to the AI6122 of Semester 1, AY2021-2022, starting from 08/2021. The instructor of this course is Prof. Sun Aixin.

The projects of this course consist of one individual Literature Review, and one group Project. The topic of them are shown below, and we do not have the specific grade of them given by the prof. Since multiple people complete the group work, I do not have the right to disclose the report and others' codes individually so that the relevant parts will be hidden, and the group project only presents part of the code and report finished by myself.

Type Topic Grade
Literature Review Chinese Spelling Check N.A. / 30.0
Group Project Data Analysis and Processing N.A. / 40.0
Quiz N.A. N.A. / 30.0

====== A C K N O W L E D G E M E N T ======

All of above projects are designed by Prof. Sun Aixin.

Owner
HT. Li
HT. Li
FAVD: Featherweight Assisted Vulnerability Discovery

FAVD: Featherweight Assisted Vulnerability Discovery This repository contains the replication package for the paper "Featherweight Assisted Vulnerabil

secureIT 4 Sep 16, 2022
Codes for NeurIPS 2021 paper "Adversarial Neuron Pruning Purifies Backdoored Deep Models"

Adversarial Neuron Pruning Purifies Backdoored Deep Models Code for NeurIPS 2021 "Adversarial Neuron Pruning Purifies Backdoored Deep Models" by Dongx

Dongxian Wu 31 Dec 11, 2022
Cereal box identification in store shelves using computer vision and a single train image per model.

Product Recognition on Store Shelves Description You can read the task description here. Report You can read and download our report here. Step A - Mu

Nicholas Baraghini 1 Jan 21, 2022
How to train a CNN to 99% accuracy on MNIST in less than a second on a laptop

Training a NN to 99% accuracy on MNIST in 0.76 seconds A quick study on how fast you can reach 99% accuracy on MNIST with a single laptop. Our answer

Tuomas Oikarinen 42 Dec 10, 2022
ISNAS-DIP: Image Specific Neural Architecture Search for Deep Image Prior [CVPR 2022]

ISNAS-DIP: Image-Specific Neural Architecture Search for Deep Image Prior (CVPR 2022) Metin Ersin Arican*, Ozgur Kara*, Gustav Bredell, Ender Konukogl

Özgür Kara 24 Dec 18, 2022
Official implementation for Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder at NeurIPS 2020

Likelihood-Regret Official implementation of Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder at NeurIPS 2020. T

Xavier 33 Oct 12, 2022
2D&3D human pose estimation

Human Pose Estimation Papers [CVPR 2016] - 201511 [IJCAI 2016] - 201602 Other Action Recognition with Joints-Pooled 3D Deep Convolutional Descriptors

133 Jan 02, 2023
An Straight Dilated Network with Wavelet for image Deblurring

SDWNet: A Straight Dilated Network with Wavelet Transformation for Image Deblurring(offical) 1. Introduction This repo is not only used for our paper(

FlyEgle 41 Jan 04, 2023
Tutorial: Introduction to Graph Machine Learning, with Jupyter notebooks

GraphMLTutorialNLDL22 Tutorial NLDL22: Introduction to Graph Machine Learning, with Jupyter notebooks This tutorial takes place during the conference

UiT Machine Learning Group 3 Jan 10, 2022
TensorFlow implementation of "Learning from Simulated and Unsupervised Images through Adversarial Training"

Simulated+Unsupervised (S+U) Learning in TensorFlow TensorFlow implementation of Learning from Simulated and Unsupervised Images through Adversarial T

Taehoon Kim 569 Dec 29, 2022
Official code repository for Continual Learning In Environments With Polynomial Mixing Times

Official code for Continual Learning In Environments With Polynomial Mixing Times Continual Learning in Environments with Polynomial Mixing Times This

Sharath Raparthy 1 Dec 19, 2021
The aim of this project is to build an AI bot that can play the Wordle game, or more generally Squabble

Wordle RL The aim of this project is to build an AI bot that can play the Wordle game, or more generally Squabble I know there are more deterministic

Aditya Arora 3 Feb 22, 2022
PyTorch implementation of SIFT descriptor

This is an differentiable pytorch implementation of SIFT patch descriptor. It is very slow for describing one patch, but quite fast for batch. It can

Dmytro Mishkin 150 Dec 24, 2022
Code for the SIGGRAPH 2021 paper "Consistent Depth of Moving Objects in Video".

Consistent Depth of Moving Objects in Video This repository contains training code for the SIGGRAPH 2021 paper "Consistent Depth of Moving Objects in

Google 203 Jan 05, 2023
The final project of "Applying AI to 3D Medical Imaging Data" from "AI for Healthcare" nanodegree - Udacity.

Quantifying Hippocampus Volume for Alzheimer's Progression Background Alzheimer's disease (AD) is a progressive neurodegenerative disorder that result

Omar Laham 1 Jan 14, 2022
Open source simulator for autonomous vehicles built on Unreal Engine / Unity, from Microsoft AI & Research

Welcome to AirSim AirSim is a simulator for drones, cars and more, built on Unreal Engine (we now also have an experimental Unity release). It is open

Microsoft 13.8k Jan 05, 2023
PyTorch implementation of Off-policy Learning in Two-stage Recommender Systems

Off-Policy-2-Stage This repo provides a PyTorch implementation of the MovieLens experiments for the following paper: Off-policy Learning in Two-stage

Jiaqi Ma 25 Dec 12, 2022
TensorFlow Implementation of Unsupervised Cross-Domain Image Generation

Domain Transfer Network (DTN) TensorFlow implementation of Unsupervised Cross-Domain Image Generation. Requirements Python 2.7 TensorFlow 0.12 Pickle

Yunjey Choi 864 Dec 30, 2022
PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)

English | 简体中文 Welcome to the PaddlePaddle GitHub. PaddlePaddle, as the only independent R&D deep learning platform in China, has been officially open

19.4k Jan 04, 2023
for a paper about leveraging discourse markers for training new models

TSLM-DISCOURSE-MARKERS Scope This repository contains: (1) Code to extract discourse markers from wikipedia (TSA). (1) Code to extract significant dis

International Business Machines 6 Nov 02, 2022