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Introduction:

A repository dedicated to implement many sorts of algorithms in Machine Learning, Deep Learning and Reinforcement Learning using TensorFlow 2 (emphasising heavily in this library) and many other libraries.

Algorithms:

[x] Machine Learning:

  • Linear Regression
  • Kernel Linear Regression
  • Logistic Regression (0,1)
  • Logistic Regression (-1,1)
  • Kernel Logistic Regression
  • K Nearest Neighbours
  • K Means Clustering
  • Naive Bayes Classifier
  • Linear Support Vector Machine
  • Non Linear Support Vector Machine

[x] Computer Vision:

  • Auto-encoders
    • Vanilla Autoencoder
    • Convolutional Autoencoder
    • Sparse Autoencoder
    • Stacked Autoencoder
    • Denoise Autoencoder
    • Variational Autoencoder
    • Contractive Autoencoder
    • Adversarial Autoencoder
    • Self-attention Autoencoder
    • Recurrent Autoencoder
    • Sparse Variational Autoencoder
    • Beta Variational Autoencoder
    • Transformative Autoencoder
  • Generative Adversarial Network
    • Deep ANN GAN
    • Deep Convolutional GAN
    • Conditional GAN
    • Least Square GAN
    • Wasserstein GAN
    • Wasserstein Improved GAN
    • Deep Regret Analytic GAN
    • Cycle GAN
    • Star GAN
    • Super Resolution GAN
  • Image Classification
    • Large Network
      • AlexNet
      • VGG Net
      • Inception Net
        • Inception V1 (Google Net)
        • Inception V2
        • Inception V3
        • Inception V4
      • Residual Net
      • Res Next
      • SeNet
      • Dense Net
      • Highway Net
      • Network In Network
      • Vision Transformer
      • Residual Attention Net
      • Capsule Network
    • Small Network
      • LeNet
      • ZFNet
      • Deep Compression
      • Knowledge Distillation
      • MLP-Mixer
      • Mobile Net
      • Poly Net
      • Shuffle Net
      • Squeeze Net
      • Xception Net
      • XNOR-Net
    • Robustness
      • Adversarial Saliency Maps
      • Black Box Methods
      • Fast Gradient Sign Method
      • Iterative Least Likely Method
  • Miscellaneous
    • Genetic CNN
    • Style Transfer
    • Empirical Risk Minimisation
    • Gaussian CDF
    • Gradient Accumulation
    • Gradient test for Initialisation
    • Regularisation with Nelder Mead Optimisation

[x] Reinforcement Learning:

  • Memory:
    • Replay Buffer
    • Non Buffer
    • Prioritised Experience Replay
  • Strategies:
    • Value Based:
      • DQN
      • Double DQN
      • Duelling DQN
      • Double Duelling DQN
      • Rainbow
      • C51
    • Policy Based:
      • PG (vanilla)
      • Reinforce
      • Trusted Region PO (TRPO)
      • Proximal PO (PPO)
      • ACKTR
    • Actor Critic Based:
      • Vanilla AC
      • Advantageous AC (A2C)
      • Asynchronous Advanatageous AC (A3C)
      • Soft AC (SAC)
      • Deep Deterministic PG (DDPG)
      • Twin Delayed DDPG (TD3)

Contributions

Contributions are welcome! If you have implemented a new insights or have improvements to existing implementations, feel free to submit a pull request. Please follow the contribution guidelines outlined in the repository.

License

This project is licensed under the GNU General Public License v3.0 - see the LICENSE file for details.

Happy generating!