In this article, we will make a mathematical model of a disease spreading in a population, and observe the effect of immune people on the spreading of the disease.
Memorizing is not learning! — 6 tricks to prevent overfitting in machine learning.
Overfitting may be the most frustrating issue of Machine Learning. In this article, we’re going to see what it is, how to spot it, and most importantly how to prevent it from happening.
Stop Feeding Garbage To Your Model! — The 6 biggest mistakes with datasets and how to avoid them.
Learn how to build killer datasets by avoiding the most frequent mistakes in Data Science, plus tips, tricks and kittens.
Teaching a robot how to walk with Q-Learning
Today, we’re gonna learn how to create a virtual agent that discovers how to interact with the world. The technique we’re going to use is called Q-Learning, and it’s super cool.
Adversarial Examples and their implications
In this article, we are going to talk about adversarial attacks and discuss their implications for deep learning model and their security.
Latent space visualization
Today, we will see how autoencoders can help us visualize the data in some very cool ways. For that, we will work on images, using the Convolutional Autoencoder architecture (CAE).
Autoencoders
Autoencoders (AE) are a family of neural networks for which the input is the same as the output*. They work by compressing the input into a latent-spacerepresentation, and then reconstructing the output from this representation.
Commanding your computer with your eyes and Deep Learning
Have you ever found yourself eating, with no free hands to change the volume of your movie? Or the brightness of the screen? We’ll see how to use state-of-the-art artificial intelligence techniques to solve this problem by sending commands your computer with eye movements!
Finding the genre of a song with Deep Learning
A step-by-step guide to make your computer a music expert.