Today we want to build a model, that can identify ingredients in cooking recipes. I use the “German Recipes Dataset”, I recently published on kaggle. We have more than 12000 German recipes and their ingredients list. Read more

This is the first post of my series about understanding text datasets. A lot of the current NLP progress is made in predictive performance. But in practice, you often want and need to know, what is going on in your dataset. Read more

In the last post, I introduced the U-Net model for segmenting salt depots in seismic images. This time, we will see how to improve the model by data augmentation and especially test time augmentation (TTA). You will learn how to use data augmentation with segmentation masks and what test time augmentation is and how to use it in keras. Read more

Today I’m going to write about a kaggle competition I started working on recently. In the TGS Salt Identification Challenge, you are asked to segment salt deposits beneath the Earth’s surface. So we are given a set of seismic images that are $101 \times 101$ pixels each and each pixel is classified as either salt or sediment. Read more

Word vectors Today, I tell you what word vectors are, how you create them in python and finally how you can use them with neural networks in keras. For a long time, NLP methods use a vectorspace model to represent words. Read more

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, augmentation, pre-trained models for transfer learning and fine-tuning. Read more

This time we’re going to discuss a current machine learning completion on kaggle. In this competition, you’re challenged to build a multi-headed model that’s capable of detecting different types of of toxicity like threats, obscenity, insults, and identity-based hate. Read more