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Introduction to week 3
A short introductory article to week 3 of the course Deep Learning for Bioscientists - training convolutional neural networks
Welcome to Week 3 of the course.
Once we have built a network using the software tool of choice (we are using PyTorch), the next step is to train the network with the available data. This is done by comparing the network output with the desired output we have annotated within the data, as we will see in more detail in the following videos and activities.
In this week we will look at:
- the training loop – key steps for training a network
- hyperparameters – adjusting the training process to make improvements
- datasets and dataloaders – organising large datasets efficiently.
Week 3 learning outcomes
- Perform the basic steps needed to train a deep learning model
- Improve the deep learning training process by adjusting hyperparameters
