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

Last update: Dec 26, 2022

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.

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

Related tags

Overview

Machine Learning 2021

Homeworks

Viewing Jupyter notebook

Download Google Drive files with WGET

Achievement

Owner

This is a pytorch implementation of the NeurIPS paper GAN Memory with No Forgetting.

AI-based, context-driven network device ranking

Differential Privacy for Heterogeneous Federated Learning : Utility & Privacy tradeoffs

JAX code for the paper "Control-Oriented Model-Based Reinforcement Learning with Implicit Differentiation"

code for paper "Not All Unlabeled Data are Equal: Learning to Weight Data in Semi-supervised Learning" by Zhongzheng Ren, Raymond A. Yeh, Alexander G. Schwing.

A collection of IPython notebooks covering various topics.

A Peer-to-peer Platform for Secure, Privacy-preserving, Decentralized Data Science

Entity-Based Knowledge Conflicts in Question Answering.

Faster RCNN with PyTorch

Fast, modular reference implementation of Instance Segmentation and Object Detection algorithms in PyTorch.

Implementation of paper "Towards a Unified View of Parameter-Efficient Transfer Learning"

A lightweight Python-based 3D network multi-agent simulator. Uses a cell-based congestion model. Calculates risk, loudness and battery capacities of the agents. Suitable for 3D network optimization tasks.

The undersampled DWI image using Slice-Interleaved Diffusion Encoding (SIDE) method can be reconstructed by the UNet network.

This is an example implementation of the paper "Cross Domain Robot Imitation with Invariant Representation".

SynNet - synthetic tree generation using neural networks

Source code of AAAI 2022 paper "Towards End-to-End Image Compression and Analysis with Transformers".

Fully convolutional networks for semantic segmentation

Code release for NeurIPS 2020 paper "Co-Tuning for Transfer Learning"

This is the official implement of paper "ActionCLIP: A New Paradigm for Action Recognition"

Self-Supervised Learning with Kernel Dependence Maximization

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

Related tags

Overview

Machine Learning 2021

Homeworks

Viewing Jupyter notebook

Download Google Drive files with WGET

Achievement

Owner

This is a pytorch implementation of the NeurIPS paper GAN Memory with No Forgetting.

AI-based, context-driven network device ranking

Differential Privacy for Heterogeneous Federated Learning : Utility & Privacy tradeoffs

JAX code for the paper "Control-Oriented Model-Based Reinforcement Learning with Implicit Differentiation"

code for paper "Not All Unlabeled Data are Equal: Learning to Weight Data in Semi-supervised Learning" by Zhongzheng Ren*, Raymond A. Yeh*, Alexander G. Schwing.

A collection of IPython notebooks covering various topics.

A Peer-to-peer Platform for Secure, Privacy-preserving, Decentralized Data Science

Entity-Based Knowledge Conflicts in Question Answering.

Faster RCNN with PyTorch

Fast, modular reference implementation of Instance Segmentation and Object Detection algorithms in PyTorch.

Implementation of paper "Towards a Unified View of Parameter-Efficient Transfer Learning"

A lightweight Python-based 3D network multi-agent simulator. Uses a cell-based congestion model. Calculates risk, loudness and battery capacities of the agents. Suitable for 3D network optimization tasks.

The undersampled DWI image using Slice-Interleaved Diffusion Encoding (SIDE) method can be reconstructed by the UNet network.

This is an example implementation of the paper "Cross Domain Robot Imitation with Invariant Representation".

SynNet - synthetic tree generation using neural networks

Source code of AAAI 2022 paper "Towards End-to-End Image Compression and Analysis with Transformers".

Fully convolutional networks for semantic segmentation

Code release for NeurIPS 2020 paper "Co-Tuning for Transfer Learning"

This is the official implement of paper "ActionCLIP: A New Paradigm for Action Recognition"

Self-Supervised Learning with Kernel Dependence Maximization

code for paper "Not All Unlabeled Data are Equal: Learning to Weight Data in Semi-supervised Learning" by Zhongzheng Ren, Raymond A. Yeh, Alexander G. Schwing.