Posted on Thu 03 May 2018 in Experiments • Tagged with Deep Learning, Style Transfer
In this article we'll decode the research article with the same name and get some cool results integrating random objects in paintings while preserving their style.
Posted on Thu 26 April 2018 in Experiments • Tagged with Deep Learning, NLP
You can easily boost the performance of a language model based on RNNs by adding a pointer cache on top of it. The idea was introduce by Grave et al. and their results showed how this simple technique can make your perplexity decrease by 10 points without additional training. This sounds exciting, so let's see what this is all about and implement that in pytorch with the fastai library.
Posted on Sat 14 April 2018 in Basics • Tagged with Deep Learning, NLP
In Natural Language Processing, traditional neural networks struggle to properly execute the task we give them. To predict the next work in a sentence for instance, or grasp its meaning to somehow classify it, you need to have a structure that can keeps some memory of the words it saw before. That's why Recurrent Neural Network have been designed to do, and we'll look into them in this article.
Posted on Sat 07 April 2018 in Experiments • Tagged with Deep Learning, SGD, Learning Rate
Properly setting the hyper-parameters of a neural network can be challenging, fortunately, there are some recipe that can help.
Posted on Thu 05 April 2018 in Basics • Tagged with Deep Learning, Convolution
CNNs (Convolutional Neural Network) are the most powerful networks used in computer vision. Let's see what a convolutional layer is all about, from the definition to the implementation in numpy, even with the back propagation.
Posted on Thu 29 March 2018 in Basics • Tagged with SGD, Deep Learning
Posted on Tue 20 March 2018 in Basics • Tagged with Neural Net, Back Propagation
Now that we have seen how to build a neural net in pytorch, let's try to take it a step further and try to do the same thing in numpy.
Posted on Tue 20 March 2018 in Basics • Tagged with SGD, Learning Rate
This is the main hyper-parameter to set when we train a neural net, but how do you determine the best value? Here's a technique to quickly decide on one.
Posted on Fri 16 March 2018 in Basics • Tagged with Neural net, Pytorch, Deep learning
The theory is all really nice, but let's actually build a neural net and train it! We'll see how a simple neural net with one hidden layer can learn to recognize digits very efficiently.
Posted on Tue 13 March 2018 in Basics • Tagged with Neural Net, SGD, Deep Learning
What is deep learning? It's a class of algorithms where you train something called a neural net to complete a specific task. Let's begin with a general overview and we will dig into the details in subsequent articles.