[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
meProp: Sparsified Back Propagation for Accelerated Deep Learning

meProp The codes were used for the paper meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting (ICML 2017) [pdf]

LancoPKU 107 Nov 18, 2022
NovelD: A Simple yet Effective Exploration Criterion

NovelD: A Simple yet Effective Exploration Criterion Intro This is an implementation of the method proposed in NovelD: A Simple yet Effective Explorat

29 Dec 05, 2022
PyTorch implementation of SmoothGrad: removing noise by adding noise.

SmoothGrad implementation in PyTorch PyTorch implementation of SmoothGrad: removing noise by adding noise. Vanilla Gradients SmoothGrad Guided backpro

SSKH 143 Jan 05, 2023
Implementation of the master's thesis "Temporal copying and local hallucination for video inpainting".

Temporal copying and local hallucination for video inpainting This repository contains the implementation of my master's thesis "Temporal copying and

David รlvarez de la Torre 1 Dec 02, 2022
BABEL: Bodies, Action and Behavior with English Labels [CVPR 2021]

BABEL is a large dataset with language labels describing the actions being performed in mocap sequences. BABEL labels about 43 hours of mocap sequences from AMASS [1] with action labels.

113 Dec 28, 2022
Walk with fastai

Shield: This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Walk with fastai What is this p

Walk with fastai 124 Dec 10, 2022
A Python package for performing pore network modeling of porous media

Overview of OpenPNM OpenPNM is a comprehensive framework for performing pore network simulations of porous materials. More Information For more detail

PMEAL 336 Dec 30, 2022
FinRLยญ-Meta: A Universe for Dataยญ-Driven Financial Reinforcement Learning. ๐Ÿ”ฅ

FinRL-Meta: A Universe of Market Environments. FinRL-Meta is a universe of market environments for data-driven financial reinforcement learning. Users

AI4Finance Foundation 543 Jan 08, 2023
2021 Artificial Intelligence Diabetes Datathon

A.I.D.D. 2021 2021 Artificial Intelligence Diabetes Datathon A.I.D.D. 2021์€ โ€˜2021 ์ธ๊ณต์ง€๋Šฅ ํ•™์Šต์šฉ ๋ฐ์ดํ„ฐ ๊ตฌ์ถ•์‚ฌ์—…โ€™์„ ํ†ตํ•ด ๋งŒ๋“ค์–ด์ง„ ํ•™์Šต์šฉ ๋ฐ์ดํ„ฐ๋ฅผ ํ™œ์šฉํ•˜์—ฌ ๋‹น๋‡จ๋ณ‘์„ ํšจ๊ณผ์ ์œผ๋กœ ์˜ˆ์ธกํ•  ์ˆ˜ ์žˆ๋Š”๊ฐ€์— ๋Œ€ํ•œ A

2 Dec 27, 2021
Official PyTorch Implementation of Hypercorrelation Squeeze for Few-Shot Segmentation, arXiv 2021

Hypercorrelation Squeeze for Few-Shot Segmentation This is the implementation of the paper "Hypercorrelation Squeeze for Few-Shot Segmentation" by Juh

Juhong Min 165 Dec 28, 2022
Materials for my scikit-learn tutorial

Scikit-learn Tutorial Jake VanderPlas email: [email protected] twitter: @jakevdp gith

Jake Vanderplas 1.6k Dec 30, 2022
Unofficial TensorFlow implementation of the Keyword Spotting Transformer model

Keyword Spotting Transformer This is the unofficial TensorFlow implementation of the Keyword Spotting Transformer model. This model is used to train o

Intelligent Machines Limited 8 May 11, 2022
Semantic Segmentation Architectures Implemented in PyTorch

pytorch-semseg Semantic Segmentation Algorithms Implemented in PyTorch This repository aims at mirroring popular semantic segmentation architectures i

Meet Shah 3.3k Dec 29, 2022
An implementation demo of the ICLR 2021 paper Neural Attention Distillation: Erasing Backdoor Triggers from Deep Neural Networks in PyTorch.

Neural Attention Distillation This is an implementation demo of the ICLR 2021 paper Neural Attention Distillation: Erasing Backdoor Triggers from Deep

Yige-Li 84 Jan 04, 2023
Official repository for Fourier model that can generate periodic signals

Conditional Generation of Periodic Signals with Fourier-Based Decoder Jiyoung Lee, Wonjae Kim, Daehoon Gwak, Edward Choi This repository provides offi

8 May 25, 2022
Bounding Wasserstein distance with couplings

BoundWasserstein These scripts reproduce the results of the article Bounding Wasserstein distance with couplings by Niloy Biswas and Lester Mackey. ar

Niloy Biswas 1 Jan 11, 2022
Tree LSTM implementation in PyTorch

Tree-Structured Long Short-Term Memory Networks This is a PyTorch implementation of Tree-LSTM as described in the paper Improved Semantic Representati

Riddhiman Dasgupta 529 Dec 10, 2022
The 2nd Version Of Slothybot

SlothyBot Go to this website: "https://bitly.com/SlothyBot" The 2nd Version Of Slothybot. The Bot Has Many Features, Such As: Moderation Commands; Kic

Slothy 0 Jun 01, 2022
An implementation for `Text2Event: Controllable Sequence-to-Structure Generation for End-to-end Event Extraction`

Text2Event An implementation for Text2Event: Controllable Sequence-to-Structure Generation for End-to-end Event Extraction Please contact Yaojie Lu (@

Roger 153 Jan 07, 2023
RODD: A Self-Supervised Approach for Robust Out-of-Distribution Detection

RODD Official Implementation of 2022 CVPRW Paper RODD: A Self-Supervised Approach for Robust Out-of-Distribution Detection Introduction: Recent studie

Umar Khalid 17 Oct 11, 2022