In our previous post, we gave you an overview of the differences between Keras and PyTorch, aiming to help you pick the framework that’s better suited to your needs. Now, it’s time for a trial by combat. We’re going to pit Keras and PyTorch against each other, showing their strengths and weaknesses in action. We present a real problem, a matter of life-and-death: distinguishing Aliens from Predators!
For companies seeking ways to test AI-driven solutions in a safe environment, running a competition for data scientists is a great and affordable way to go – when it’s done properly. According to a McKinsey report, only 20% of companies consider themselves adopters of AI technology while 41% remain uncertain about the benefits that AI […]
Everybody who watched ‘Minority Report’ daydreams about crime forecasting in the real world. We have good news: machine learning algorithms can do that!
In this post we present how to approach product recognition through the example of our solution for the iMaterialist challenge announced by CVPR and Google.
In the previous post we explained what region of interest pooling (RoI pooling for short) is. In this one, we present an example of applying RoI pooling in TensorFlow. We base it on our custom RoI pooling TensorFlow operation. We also use Neptune as a support in our experiment performance tracking.
Internal validation is a useful tool for comparing results of experiments performed by team members in any business or research task. It can also be a valuable complement of public leaderboards attached to machine learning competitions on platforms like Kaggle. In this post, we present how to build an internal validation leaderboard using Python scripts […]
