Download the files for Lab 2B from the following links: We recommend that you use Google Colab, as training will be faster on the GPU. To enable the GPU on Colab, go to Edit / Notebook settings / Hardware accelerator / select T4 GPU Instructions on how to download and use Jupyter Notebooks can be … Read more
Download the Jupyter Notebook for this lab in the following link. Download the data for the lab in the following link . Instructions on how to download and use Jupyter Notebooks can be found here. You can find a static version of the notebook below. Lab2B_notebook Convolutional Neural Networks¶ A convolutional neural network (CNN) is … Read more
Welcome to WordPress. This is your first post. Edit or delete it, then start writing!
Using linear parameterizations can be seen to fail even when the model is linear if we don’t have enough data. In this post, we will see that neural networks (NN) can success in learning non-linear models, but this is only true if we have sufficient data. In this post we will work with the simplest … Read more
Download in pdf format We consider a learning problem with input observations $\bbx\in\reals^n$ and output information $\bby\in\reals^m$. We use a linear learning parametrization that we want to train to predict outputs as $\hby=\bbH\bbx$ that are close to the real $\bby$. The comparison metric between $\bby$ and $\hby$ is the squared Euclidean error $\ell(\bby, \hby) = … Read more
We can define convolutions for time signals, convolutions for images, and convolutions on graphs. These three operations have deep connections that we explore in this post.
Read this post if you want to find out about the papers on which this course is based.
