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' ...
The life of a machine learning engineer consists of long stretches of frustration and a few moments of joy! First, struggle to get your model to produce good results on your training data. You ...
Deep learning based models have achieved the state of the art performance for image recognition and object detection tasks in the recent past. Many of these models are able to achieve human level ...
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 ...
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 ...
Imagine you trained a deep learning model on some dataset. A few days later, you want to reproduce the same experiment, but if you were not careful, you may never be able to reproduce the same ...
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