miguelgfierro / ai_projects

What it does

• Introduction to Convolutional Neural Networks. In this project we explain what is a convolution and how to compute a CNN using MXNet deep learning library with the MNIST character recognition dataset. Here the blog entry.
• Introduction to Transfer Learning. In this project we use PyTorch to explain the basic methodologies of transfer learning (finetuning and freezing) and analyze in which case is better to use each of them. Here the blog entry.
• Cloud-Scale Text Classification With Convolutional Neural Networks: In these notebooks we show how to perform character level convolutions for sentiment analysis using Char-CNN and VDCNN models. Here the blog entry.
• Introduction to Data Generation. In this notebook we show a number of simple techniques to generate new data in images, text and time series. Here the blog entry.
• Introduction to Dimensionality Reduction with t-SNE: In this project we use sklearn and CUDA to show an example of t-SNE algorithm. We use a CNN to generate high-dimensional features from images and then show how they can be projected and v