This time I will show you how to build a simple “AI” product with transfer learning. We will build a “dog breed identification chat bot”. In this first post, I will show how to build a good model using keras,… Continue Reading →
In this post, I will show you how to use the isolation forest algorithm to detect attacks to computer networks in python.
This time we’re going to discuss a current machine learning competion on kaggle. In this competition, you’re challenged to build a model that’s capable of detecting different types of toxicity in comments from Wikipedia’s talk page edits. I will show you how to create a strong baseline using python and keras.
I show a state-of-the-art approach to named entity recognition. A hybrid approach combining a bidirectional LSTM model and a CRF model
This is the third post in my series about named entity recognition. If you haven’t seen the last two, have a look now. The last time we used a conditional random field to model the sequence structure of our… Continue Reading →
This is the second post in my series about named entity recognition. This time, we’re going to look into a more sophisticated algorithm, a so called conditional random field.
In this post you will learn how to do basic Named Entity Recognition (NER) in python. This is the first post in a series about NER.
Today we will apply the concept of multi-label multi-class classification with neural networks from the last post to
classify movie posters by genre.
Often in machine learning tasks, you have multiple possible labels for one sample that are not mutually exclusive. This is called a multi-class, multi-label classification problem. Obvious suspects are image classification and text classification, where a document can have multiple… Continue Reading →