In this article, I’m going to build an app that recognizes handwritten digits from the famous MNIST machine learning dataset: The MNIST challenge requires machine learning models to read images of handwritten digits and correctly predict which digit is visible in each image. This may seem like an easy challenge…

In this article, I am going to build an F# app with ML.NET and NET Core that reads medical data and predicts if a patient has a risk of heart disease. I will show you how to do this with only 120 lines of code. ML.NET is Microsoft’s new machine…

Building machine learning apps has never been easier! Because we have ML.NET, Microsoft’s new machine learning library. It can run linear regression, logistic classification, clustering, deep learning, and many other machine learning algorithms. But did you know that the F# language is the perfect choice for developing machine learning applications…

In this article I’m going to build a specialized neural network architecture called a Generative Adversarial Network (GAN). GANs are weird. Here’s what they look like: The Generator is a convolutional neural network (CNN) laid out in reverse. A normal CNN reads in an image and outputs a list of…

Style transfer is a process where we recompose an image in the style of another image by transferring the artistic style from one picture to another using a convolutional neural network. It looks like this: This is a photo of Pablo Picasso painting a bull on a sheet of glass…

In this article I’m going to build an app that can automatically detect the sentiment of an English text. I actually tried this already in this article where I used a 1-dimensional convolutional neural network to analyze the movie review text. …

In this article I’m going to build an app that can automatically detect the sentiment of IMDB movie reviews. The first thing I’ll need is a dataset with thousands of movie reviews, correctly labelled as having positive of negative sentiment. The Kaggle IMDB dataset has exactly what I need. It’s…

In the TV show Silicon Valley there’s a famous scene where Jian-Yang demonstrates the SeeFood app that can identify any kind of food in an image. Of course, this being Silicon Valley, there’s a catch: the app can only identify hotdogs and classifies everything else as ‘not hotdog’. Watch the…

Spam is becoming a huge problem. Last year, 53.5% of all email traffic worldwide was due to spam messages, with the most common topics being healthcare and dating. Imagine how much bandwidth and electricity is being wasted here! So let’s see if we can solve this problem. In this article…