My coursework for Machine Learning (2021 Spring) at National Taiwan University (NTU)

Overview

Machine Learning 2021

Machine Learning (NTU EE 5184, Spring 2021)

Instructor: Hung-yi Lee

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


Homeworks

# Homework Public score Private Score Score Ranking*
1 Regression 0.87985 0.91099 9 Top 35% (709/2032)
2 Classification 0.76324 0.76319 10.5 Top 5% (59/1522)
3 CNN 0.83094 0.82546 10.5 Top 7% (87/1404)
4 Self-Attention 0.96857 0.96888 10.5 Top 7% (81/1170)
5 Transformer 33.53 32.27 10.5 Top 1% (11/1110)
6 GAN (0.688, 7722.47) NA 10.5 Top 41% (405/1118)
7 BERT 0.85926 0.85157 10.5 Top 4% (39/1263)
8 Anomaly Detection 0.90118 0.89286 10.5 Top 9% (104/1193)
9 Explainable AI NA NA 9.7 NA
10 Attack 0.010 0.010 10.5 Top 14% (154/1162)
11 Adaptation 0.78806 0.78744 10 Top 26% (268/1061)
12 RL 287 NA 10.5 Top 2% (10/766)
13 Compression 0.75686 0.75493 9.5 Top 19% (109/590)
14 Life-Long Learning NA NA 9.2 NA
15 Meta Learning NA NA 10 NA

*Ranking is based on private leaderboard


Viewing Jupyter notebook

Sometimes the error message "Sorry, something went wrong. Reload?" appears when viewing *.ipynb on a GitHub.

We recommend using nbviewer to view the *.ipynb files

Simply copy the URL of this repository to https://nbviewer.jupyter.org/

Download Google Drive files with WGET

Example of a Google Drive download link (HW3 data): https://drive.google.com/file/d/1awF7pZ9Dz7X1jn1_QAiKN-_v56veCEKy/view

The url has the following format https://drive.google.com/file/d/[ID]/view

Copy the ID and run the script wgetgdrive.sh as follows

chmod a+x ./wgetgdrive.sh
./wgetgdrive.sh [ID] [file_name]

For example, to download the data of HW3 and name it as food-11.zip, simply run the following

chmod a+x ./wgetgdrive.sh
./wgetgdrive.sh 1awF7pZ9Dz7X1jn1_QAiKN-_v56veCEKy food-11.zip

Achievement

I finish the 15 assignments with all scores above 9 pts and win a T-shirt as a prize. Only the top 2% (17/1280) students own such an achievement.

shirt

Owner
National Taiwan University. M.S. in Electrical Engineering, 2021
[ICCV 2021] Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identification

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"NAS-Bench-301 and the Case for Surrogate Benchmarks for Neural Architecture Search".

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This repository contains code for the paper Scalable One-Pass Optimisation of High-Dimensional Weight-Update Hyperparameters by Implicit Differentiati

8 Aug 28, 2022
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SSAN Introduction This is the pytorch implementation of the SSAN model (see our AAAI2021 paper: Entity Structure Within and Throughout: Modeling Menti

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PyTorch code for 'Efficient Single Image Super-Resolution Using Dual Path Connections with Multiple Scale Learning'

Efficient Single Image Super-Resolution Using Dual Path Connections with Multiple Scale Learning This repository is for EMSRDPN introduced in the foll

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Self-supervised Augmentation Consistency for Adapting Semantic Segmentation (CVPR 2021)

Self-supervised Augmentation Consistency for Adapting Semantic Segmentation This repository contains the official implementation of our paper: Self-su

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Meshed-Memory Transformer for Image Captioning. CVPR 2020

M²: Meshed-Memory Transformer This repository contains the reference code for the paper Meshed-Memory Transformer for Image Captioning (CVPR 2020). Pl

AImageLab 422 Dec 28, 2022
BMVC 2021: This is the github repository for "Few Shot Temporal Action Localization using Query Adaptive Transformers" accepted in British Machine Vision Conference (BMVC) 2021, Virtual

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This code is an implementation for Singing TTS.

MLP Singer This code is an implementation for Singing TTS. The algorithm is based on the following papers: Tae, J., Kim, H., & Lee, Y. (2021). MLP Sin

Heejo You 22 Dec 23, 2022
Weighted K Nearest Neighbors (kNN) algorithm implemented on python from scratch.

kNN_From_Scratch I implemented the k nearest neighbors (kNN) classification algorithm on python. This algorithm is used to predict the classes of new

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The first machine learning framework that encourages learning ML concepts instead of memorizing class functions.

SeaLion is designed to teach today's aspiring ml-engineers the popular machine learning concepts of today in a way that gives both intuition and ways of application. We do this through concise algori

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This project demonstrates the use of neural networks and computer vision to create a classifier that interprets the Brazilian Sign Language.

LIBRAS-Image-Classifier This project demonstrates the use of neural networks and computer vision to create a classifier that interprets the Brazilian

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