My course projects for the 2021 Spring Machine Learning course at the National Taiwan University (NTU)

Last update: Aug 29, 2022

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Deep Learning ML2021Spring

Overview

ML2021Spring

There are my projects for the 2021 Spring Machine Learning course at the National Taiwan University (NTU)

Course Web : https://speech.ee.ntu.edu.tw/~hylee/ml/2021-spring.html

Instructor: Hung-yi Lee

Note :

All of the projects run on Jupter Notebook(.ipynb ), remember to adjust the environment setting ( Colab drive mount, file directory... ) before you use it
To get the source data, you can reference the content in each project file or the slide of each project introduction on course web
I mainly focus on understanding the concept and the implementation of the related models, you can further enhance the result by adjusting model architecture/parameters yourself : )

Course Porjects

Num	Topic	Model	Public Score	Private Score
1	COVID-19 Cases Prediction	Regression	0.89477	0.91152
2	Phoneme Classification	Classification	0.74934	0.74925
3	Food Classification	CNN	0.82437	0.81829
4	Speaker Classification	Self-Attention	0.95595	0.95333
5	Neural Machine Translation	Transformer	N/A	N/A
6	Anime Face Generation	GAN	N/A	N/A
7	Question Answering	BERT	0.82723	0.82979
12	Lunar Lander	Reinforcement Learning	N/A	N/A

Score is the test result from the opened kaggle platform, N/A means the test platform is not opened to non NTU students, reference the kaggle info on course web
You can see more info and learning keywords in the corresponding project page

Owner

Ding-Li Chen

Ding-Li Chen

GitHub Repository

Implementation of ETSformer, state of the art time-series Transformer, in Pytorch

ETSformer - Pytorch Implementation of ETSformer, state of the art time-series Transformer, in Pytorch Install $ pip install etsformer-pytorch Usage im

121 Dec 30, 2022

Data and Code for paper Outlining and Filling: Hierarchical Query Graph Generation for Answering Complex Questions over Knowledge Graph is available for research purposes.

Data and Code for paper Outlining and Filling: Hierarchical Query Graph Generation for Answering Complex Questions over Knowledge Graph is available f

5 Nov 10, 2022

U-Net for GBM

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1 Oct 27, 2021

Use .csv files to record, play and evaluate motion capture data.

Purpose These scripts allow you to record mocap data to, and play from .csv files. This approach facilitates parsing of body movement data in statisti

21 Dec 12, 2022

This repository contains the implementation of Deep Detail Enhancment for Any Garment proposed in Eurographics 2021

Deep-Detail-Enhancement-for-Any-Garment Introduction This repository contains the implementation of Deep Detail Enhancment for Any Garment proposed in

40 Dec 13, 2022

Publication describing 3 ML examples at NSLS-II and interfacing into Bluesky

Machine learning enabling high-throughput and remote operations at large-scale user facilities. Overview This repository contains the source code and

4 Sep 24, 2022

(Python, R, C/C++) Isolation Forest and variations such as SCiForest and EIF, with some additions (outlier detection + similarity + NA imputation)

IsoTree Fast and multi-threaded implementation of Extended Isolation Forest, Fair-Cut Forest, SCiForest (a.k.a. Split-Criterion iForest), and regular

141 Dec 29, 2022

Experiment about Deep Person Re-identification with EfficientNet-v2

We evaluated the baseline with Resnet50 and Efficienet-v2 without using pretrained models. Also Resnet50-IBN-A and Efficientnet-v2 using pretrained on ImageNet. We used two datasets: Market-1501 and

77 Jan 03, 2023

A library of extension and helper modules for Python's data analysis and machine learning libraries.

Mlxtend (machine learning extensions) is a Python library of useful tools for the day-to-day data science tasks. Sebastian Raschka 2014-2020 Links Doc

4.2k Jan 02, 2023

[CVPR 2021 Oral] ForgeryNet: A Versatile Benchmark for Comprehensive Forgery Analysis

ForgeryNet: A Versatile Benchmark for Comprehensive Forgery Analysis ForgeryNet: A Versatile Benchmark for Comprehensive Forgery Analysis [arxiv|pdf|v

78 Dec 22, 2022

Pytorch-3dunet - 3D U-Net model for volumetric semantic segmentation written in pytorch

pytorch-3dunet PyTorch implementation 3D U-Net and its variants: Standard 3D U-Net based on 3D U-Net: Learning Dense Volumetric Segmentation from Spar

1.3k Dec 28, 2022

Rainbow DQN implementation that outperforms the paper's results on 40% of games using 20x less data 🌈

Rainbow 🌈 An implementation of Rainbow DQN which reaches a median HNS of 205.7 after only 10M frames (the original Rainbow from Hessel et al. 2017 re

31 Dec 21, 2022

Manim is an engine for precise programmatic animations, designed for creating explanatory math videos

Manim is an engine for precise programmatic animations, designed for creating explanatory math videos. Note, there are two versions of manim. This rep

49k Jan 09, 2023

Linear algebra python - Number of operations and problems in Linear Algebra and Numerical Linear Algebra

Linear algebra in python Number of operations and problems in Linear Algebra and

5 Oct 09, 2022

Deep Learning Based Fasion Recommendation System for Ecommerce

Project Name: Fasion Recommendation System for Ecommerce A Deep learning based streamlit web app which can recommened you various types of fasion prod

13 Dec 13, 2022

Official implementation of NeurIPS'21: Implicit SVD for Graph Representation Learning

isvd Official implementation of NeurIPS'21: Implicit SVD for Graph Representation Learning If you find this code useful, you may cite us as: @inprocee

16 Jan 08, 2023

PyTorch implementation of Convolutional Neural Fabrics http://arxiv.org/abs/1606.02492

PyTorch implementation of Convolutional Neural Fabrics arxiv:1606.02492 There are some minor differences: The raw image is first convolved, to obtain

25 Dec 22, 2021

Multiple Object Tracking with Yolov5!

Tracking with yolov5 This implementation is for who need to tracking multi-object only with detector. You can easily track mult-object with your well

9 Nov 08, 2022

PyTorch Connectomics: segmentation toolbox for EM connectomics

Introduction The field of connectomics aims to reconstruct the wiring diagram of the brain by mapping the neural connections at the level of individua

132 Dec 26, 2022

Advanced Signal Processing Notebooks and Tutorials

Advanced Digital Signal Processing Notebooks and Tutorials Prof. Dr. -Ing. Gerald Schuller Jupyter Notebooks and Videos: Renato Profeta Applied Media

115 Dec 13, 2022