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1. image-embeddings image-embeddings Public

   Train and tune an autoencoder model and use it later to extract features (create embeddings) from images for further machine learning applications.

   Jupyter Notebook

2. cars cars Public

   Car model recognition using lightweight neural net architectures intended for mobile applications. Training GhostNet on Stanford Cars Dataset with PyTorch.

   Python 2 1

3. GPU_tests GPU_tests Public

   Two experiments (#1 GAN image generation; #2 image classification with Resnet; both in PyTorch) to test differences in training times between free Colab GPUs and mobile/desktop GPUs.

   Jupyter Notebook 2

4. Keras_and_Shiny Keras_and_Shiny Public

   Forked from WLOGSolutions/Keras_and_Shiny

   A showcase based on the tutorial presented at ML@Enterprise Forum 2018 in Warsaw. Combining R (Shiny) and Python (Keras) to build a simple web application for image recognition.

   R