In our recent post about receptive field computation, we examined the concept of receptive fields using PyTorch. We learned receptive field is the proper tool to understand what the network 'sees' ...
CNN Fully Convolutional Image Classification (FCN CNN) with TensorFlow –
In a previous post, we covered the concept of fully convolutional neural networks (FCN) in PyTorch, where we showed how we could solve the classification task using the input image of arbitrary ...
Graph Convolutional Networks: Model Relations In Data
In an earlier post, we covered the problem of Multi Label Image Classification (MLIC) for Image Tagging. Recall that MLIC is an image classification task but unlike multi-class image ...
Federated Learning using PyTorch and PySyft
This is a a gentle introduction to federated learning --- a technique that makes machine learning more secure by training on decentralized data. We will also cover a real-life example of federated ...
Getting Started with PyTorch Lightning
Imagine, one day you have an amazing idea for your machine learning project. You write down all the details on a piece of paper- the model architecture, the optimizer, the dataset. And now you just ...
Multi-Label Image Classification with PyTorch: Image Tagging
In the previous post, we learned how to apply a fixed number of tags to images. Let’s now switch to this broader task and see how we can tackle it. In many real-life tasks, there is a set ...