I have my new blog, which I started a few months ago. Computer Science stuff. I have two posts currently: One relating to “Rule of 72” and another about “Matrix Multiplication”. I am working on a new post about Precision and Recall metrics. Feedback is welcome!
Is there any sample code to save the output of layer before final FC layer of vgg16 for all the training images and use it as input and train the FC as a linear model ? I understand the performance benefit but I have not done it before. Can you point me to any reference code ? Thanks.
I wrote my bachelor thesis about the age assessments of teenagers using MR images of their knees. This was a study for the German Research foundation to help with asylum applications in europe. It was a fun project because I needed to apply interesting image preprocessings, segmentations, regressions, transfer learning and also some shallow machine learning techniques. I was awarded this years innovation award of my university. thanks to Jeremy for his great course!
here is a quick write up on medium:
i also just open sourced the code and full thesis:
In the spirit of Cunningham’s Law, I’ve finally received permission put together a few posts about some of the more interesting topics we’re covering working. Very keen for feedback:
Here, we investigate the effect of PyTorch model ensembles by combining the top-N single models crafted during the training phase. The results demonstrate that model ensembles may significantly outperform conventional single model approaches. Moreover, the method constructs an ensemble of deep CNN models with different architectures that are complementary to each other.
I would love to be able to build a model with fast.ai library which contains such a simulated version of octopamine and compare it with the classical models. Anyone interested in neuroscience who wants to share?