What we want is a machine that can learn from experience. — Alan Turing
This repository serves as an archive of my learning journey and projects that I have embarked in the realm of Deep Learning and its applications.
Feel free to contact me if you have any queries or spot any mistakes in my implementation.
This section list out the projects in this repository.
| Subfields | Project Title | Descriptions | Keywords |
|---|---|---|---|
| CV | EfficientNetV2 with Image Classification Benchmarks | Utilizing SOTA model and training procedure on classic Image classification dataset like Fashion-MNIST and CIFAR10 using Timm running on Pytorch. |
Image Classification, EfficientNetV2, RandAugment, Progressive Learning, Timm, Pytorch, |
| Faster-RCNN Vehicles Detection | Detecting cars using Faster-RCNN with MobilenetV3 as backbone. |
Object Detection, Faster-RCNN, MobileNetV3, FPN, Timm, Pytorch, |
|
| GAN | AC-BIGGAN with CIFAR10 | Generating small coloured images with AC-BIGGAN. |
ACGAN, BIGGAN, Conditional Batch Normalization, Hinge Loss, Label Smoothing, IS, FID, Pytorch, |
| GDL_code | Forked repository while reading O'Reilly's Generative Deep Learning book. |
VAE, WGAN, WGANGP, CycleGAN, Keras, |
|
| Generative-Adversarial-Networks-Projects | Forked repository while reading PacktPublishing's Generative Adversarial Networks Projects book. |
3DGAN, cGAN, DCGAN, SRGAN, StackGAN, CycleGAN, Keras, |
|
| RL | Great Lunar Lander with DQN | Solving Lunar-Landerv2 with DQNs approach. |
DQN, DDQN, SARSA, OpenAI Gym, Keras |
| Hands-On Reinforcement Learning with Python | Coding exercise and self-made notes from the Hands-On Reinforcement Learning with Python book published by Packt. |
Reinforcement Learning, Markov Decision Process, Monte Carlo Control, Otw, |
|
| Snake-DQN | Solving Snake with DQN approach. |
DQN, Keras |
The list of standard Python3 packages that I have used for my Machine Learning projects is shown in requirements.txt.
To install all of the packages specific to each subfields, simply call the following command:
- pip
cd CV pip install -r requirements.txt
Distributed under the MIT License. See LICENSE for more information.
Zhao Wu Wong, Bryan - @LinkedIn - [email protected]
Kaggle Profile: https://www.kaggle.com/kiritowu
- Cars Object Detection Dataset: https://www.kaggle.com/sshikamaru/car-object-detection
- README Template : https://github.com/othneildrew/Best-README-Template