In Progress

Training part of a CNN Architecture on a one dataset to use weights (PyTorch)

I need to essentially train the first half of a CNN model (Resnet50) on one dataset, before taking those weights and applying them back to the Full Resnet50 Arch for the corresponding layers (i.e. first half) for continued training.

More specifically, the steps are as follows:

1) Get model (Resnet50, we will call this the full model here so the remaining instructions are clear)

2) Split this full model to obtain the first half of it (we will call this the split model)

3) Train this split model on some toy data

4) Assign weights from split model to corresponding layers of full model

Cloud computer and toy data will be provided.

Task to be completed using PyTorch and Jupyter Notebook, with comments so the method can be used again.

To be completed by 16/03/19

Skills: Algorithm, Machine Learning, Python, Pytorch, Research

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Project ID: #18918303

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