/PyTorchProjects

Use 50 models for standard datasets with PyTorch (in progress)

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PyTorchProjects

Use 50 models(or Techniques) for standard datasets with PyTorch.(In progress)

1. Computer Vision

1.1 Image Classification

1.1.1 Datasets

  • CIFAR-10

1.1.2 Models

  • EfficientNet
  • MobileNet-v2
  • MixNet

1.2 Image Generation

1.2.1 Datasets

  • CIFAR-10

1.2.2 Models

  • GAN
  • DCGAN
  • Conditional GAN

1.3 Image Representation Learning

1.3.1 Datasets

  • CIFAR-10

1.3.2 Models

  • Convolutional AutoEncoder

1.4 Few-shot Image Classification

1.4.1 Datasets

  • AT&T faces dataset

1.4.2 Models

  • Siamese Network

2. Natural Language Processing

2.1 Sentiment Analysis

2.1.1 Datasets

  • IMDb

2.1.2 Models

3. Recommender Systems

4. Graphs

4.1 Node Classification

4.1.1 Datasets

  • Cora

4.1.2 Models

Techniques

Optimizers

Datasets

  • CIFAR-10

Techniques

  • RAdam
  • Cosine Annealing Learning Rate Scheduler
  • Image Augmentation
  • tqdm
  • Half Precision
  • Warmup
  • Optuna

Ref.

GitHub links in case there is no such function in PyTorch (or PyTorch family).