Digital-Thinking
A blog about machine learning and software development
In this post I will show how to use styleGANs on larger images to create customizable images of watches. Additionally, I show how to apply styleGAN on custom data.
This post is about how to snapshot your model based on custom validation metrics. First we define the custom metric, as shown here. In this case we use the AUC score: import tensorflow as tf from sklearn.metrics import roc_auc_score def…
In 2017 and 2018 GANs have significantly contributed to the visibility of artificial intelligence. Impressive images generated by GANs have been published and one was even sold for 432 500 $ in an Christies auction. The good thing with GANs…
In the last years a lot of progress has been made in artificial intelligence. There are many exiting breakthroughs, especially in machine learning and artificial neural networks. Major accomplishments in vision, audio and natural language processing have been achieved. And…
Smaller companies and researchers do usually not have the money to invest thousands of dollars or euros into specialized deep learning hardware. You might think cloud instances like AWS EC2 or Google compute are the straightforward cheap solution, but if…
Preprocessing and data transformation are the most important parts of all machine learning pipelines. No matter what type of model you use, if the preprocessing pipeline is buggy, your model will deliver wrong predictions . This remains also true, if…
In this How-To series, I want to share my experience with machine learning models in productions environments. This starts with the general differences to typical software projects and how to acquire and deal with data sets in such projects, goes…
Keras offers some basic metrics to validate the test data set like accuracy, binary accuracy or categorical accuracy. However, sometimes other metrics are more feasable to evaluate your model. In this post I will show three different approaches to apply…
Besides computer vision, artificial neural networks (ANNs) are also very popular in natural language processing. Automatic translation or sentiment analysis of reviews are well known areas, where (recurrent) neural networks are used a lot. Around natural language understanding, there are…
Just about one year ago, I was trying to make the distinction between data science and data engineering. But in the past year a new job role has become very popular (at least I noticed it in job postings and…