[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
Face Recognition and Emotion Detector Device

Face Recognition and Emotion Detector Device Orange PI 1 Python 3.10.0 + Django 3.2.9 Project's file explanation Django manage.py Django commands hand

BootyAss 2 Dec 21, 2021
HeartRate detector with ArduinoandPython - Use Arduino and Python create a heartrate detector.

Syllabus of Contents Syllabus of Contents Introduction Of Project Features Develop With Python code introduction Installation License Developer Contac

1 Jan 05, 2022
Just playing with getting CLIP Guided Diffusion running locally, rather than having to use colab.

CLIP-Guided-Diffusion Just playing with getting CLIP Guided Diffusion running locally, rather than having to use colab. Original colab notebooks by Ka

Nerdy Rodent 336 Dec 09, 2022
[Pedestron] Generalizable Pedestrian Detection: The Elephant In The Room. @ CVPR2021

Pedestron Pedestron is a MMdetection based repository, that focuses on the advancement of research on pedestrian detection. We provide a list of detec

Irtiza Hasan 594 Jan 05, 2023
Volumetric Correspondence Networks for Optical Flow, NeurIPS 2019.

VCN: Volumetric correspondence networks for optical flow [project website] Requirements python 3.6 pytorch 1.1.0-1.3.0 pytorch correlation module (opt

Gengshan Yang 144 Dec 06, 2022
Simple, efficient and flexible vision toolbox for mxnet framework.

MXbox: Simple, efficient and flexible vision toolbox for mxnet framework. MXbox is a toolbox aiming to provide a general and simple interface for visi

Ligeng Zhu 31 Oct 19, 2019
NeurIPS 2021 Datasets and Benchmarks Track

AP-10K: A Benchmark for Animal Pose Estimation in the Wild Introduction | Updates | Overview | Download | Training Code | Key Questions | License Intr

AP-10K 82 Dec 11, 2022
TorchX is a library containing standard DSLs for authoring and running PyTorch related components for an E2E production ML pipeline.

TorchX is a library containing standard DSLs for authoring and running PyTorch related components for an E2E production ML pipeline

193 Dec 22, 2022
Collection of tasks for fast prototyping, baselining, finetuning and solving problems with deep learning.

Collection of tasks for fast prototyping, baselining, finetuning and solving problems with deep learning Installation

Pytorch Lightning 1.6k Jan 08, 2023
LBBA-boosted WSOD

LBBA-boosted WSOD Summary Our code is based on ruotianluo/pytorch-faster-rcnn and WSCDN Sincerely thanks for your resources. Newer version of our code

Martin Dong 20 Sep 19, 2022
code for our ECCV 2020 paper "A Balanced and Uncertainty-aware Approach for Partial Domain Adaptation"

Code for our ECCV (2020) paper A Balanced and Uncertainty-aware Approach for Partial Domain Adaptation. Prerequisites: python == 3.6.8 pytorch ==1.1.0

32 Nov 27, 2022
Forecasting with Gradient Boosted Time Series Decomposition

ThymeBoost ThymeBoost combines time series decomposition with gradient boosting to provide a flexible mix-and-match time series framework for spicy fo

131 Jan 08, 2023
2021-AIAC-QQ-Browser-Hyperparameter-Optimization-Rank6

2021-AIAC-QQ-Browser-Hyperparameter-Optimization-Rank6

Aigege 8 Mar 31, 2022
A Python library that provides a simplified alternative to DBAPI 2

A Python library that provides a simplified alternative to DBAPI 2. It provides a facade in front of DBAPI 2 drivers.

Tony Locke 44 Nov 17, 2021
Official implementation for the paper: Multi-label Classification with Partial Annotations using Class-aware Selective Loss

Multi-label Classification with Partial Annotations using Class-aware Selective Loss Paper | Pretrained models Official PyTorch Implementation Emanuel

99 Dec 27, 2022
Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation (NeurIPS 2021)

Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation (NeurIPS 2021) The implementation of Reducing Infromation Bottleneck for W

Jungbeom Lee 81 Dec 16, 2022
I will implement Fastai in each projects present in this repository.

DEEP LEARNING FOR CODERS WITH FASTAI AND PYTORCH The repository contains a list of the projects which I have worked on while reading the book Deep Lea

Thinam Tamang 43 Dec 20, 2022
Demo for the paper "Overlap-aware low-latency online speaker diarization based on end-to-end local segmentation"

Streaming speaker diarization Overlap-aware low-latency online speaker diarization based on end-to-end local segmentation by Juan Manuel Coria, Hervé

Juanma Coria 187 Jan 06, 2023
[ECCV 2020] XingGAN for Person Image Generation

Contents XingGAN or CrossingGAN Installation Dataset Preparation Generating Images Using Pretrained Model Train and Test New Models Evaluation Acknowl

Hao Tang 218 Oct 29, 2022
FFCV: Fast Forward Computer Vision (and other ML workloads!)

Fast Forward Computer Vision: train models at a fraction of the cost with accele

FFCV 2.3k Jan 03, 2023