This repository offers introductory materials on Google Colaboratory. The content covered is outlined below.

1. Training an MLP using TensorFlow & Keras - configuring the python environment - About the dataset

   • MNIST
   • FashinMNIST - Preapre the dataset - Hyper-Parameters
   • epochs
   • batch size
   • learning rate - Define the model - Train the model - Evaluate the model
   • Expected results
     • lower loss
     • higher accuracy
   • How to intepret results

2. Additional Resources - Training an MLP with PyTorch Ref_Multilayer_Perceptron_PyTorch.ipynb - Why GPUs are required ? - Platforms that you can use for deep learning

   • Google Colab
   • ODU Wahab Cluster
   • Dedictaed GPU env at your own lab
   • Your local machine with GPU capabiities - Designing an MLP without deep learning frameworks such as TensorFlow, Keras, PyTorch

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Rochana R. Obadage
15th April 2024