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fine-tuning-cnns

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QuickCNN is high-level library written in Python, and backed by the Keras, TensorFlow, and Scikit-learn libraries. It was developed to exercise faster experimentation with Convolutional Neural Networks(CNN). Majorly, it is intended to use the Google-Colaboratory to quickly play with the ConvNet architectures. It also allow to train on your local…

  • Updated Dec 29, 2018
  • Python

Switching from GPU to the future of Machine learning the TPU. Over 1 million images trained Resnet50 in under 20 mins compared to days or weeks on GPU and all for 0$ free on Google Colab Notebooks in Google Drive, clone repo and jump right in!!

  • Updated May 4, 2019
  • Jupyter Notebook

The provided code demonstrates transfer learning by adapting a model trained using synthetic data to classify circles, squares, and triangles to classify new shapes like stars and pentagons. By fine-tuning a pre-trained model originally designed for a different task, the repository showcases how to efficiently adapt a model to a new domain.

  • Updated Oct 16, 2024
  • Python

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