/deep_learning_practice

keras & Pytorch implemetation of deep learning models: fine-tuning approaches, dataset analysis, hyperparameter optimization, etc.

Primary LanguageJupyter Notebook

deep-learning-with-keras-and-pytorch

keras implementations

Dataset Links

Classification

  • Breast Cancer Identification - [Kaggle]
  • Sports Classifier -
  • Cyclic LR - Implemented multi-class image classification using recent networks such as Xception, NAS Net and Efficient Net with random cut-out erasing data augmentation and Cyclic Learning rate. training code and evaluation code are both present.

Segmentation

pytorch implementation

I'm noob in pytorch. So, just learning and implementing multiple github repo for pytorch.

  • Coursera IBM Pytorch - This folder contains my solution to Pytorch course by IBM on Coursera. It contain topics of tensor_tutorial, space-stretching, autograd, spiral_classification, regression and kernel implementations. Assignments

  • Pytorch code practice - basics, linear regression, logistic regression, feedforward_nn, conv_nn, residual_network, rnn, bidirectional rnn, language models, GANs, VAEs, style transfer and image captioning. Link

Note

  • If the Jupyter notebook file is not loading, please load the notebook link on NBViewer. It is the problem from Github side.