- 01/ Introduction
- 02/ Opinions on AI related topics
- 03/ Scientific reflections from our research engineers
- 04/ Latest from the product team
Our team has aeons of experience from product and business development, as well as from academic research within AI and deep learning. In this section our team members share insights from our different areas.
03/ Scientific reflections from our research engineers
Science Introducing AI to the cancer treatment process: a driving force in the fight against cancer Illustrating the potential in using AI to empower humans in their everyday tasks - discover how to create a deep learning model for brain tumor segmentation
04/ Latest from the product team
Product Update Six latest features added to the Peltarion Platform The December sprint includes a faster and more comprehensive deployment function, a new set of available deep neural network snippets and randomized compiler options. Let’s dive in and see what other advancements have been made.
Product Features Snippets – your gateway to deep neural network architectures We’ve pre-built many of the most commonly used neural networks on the Peltarion Platform - making it easier to use large networks, without actually having to build them yourself! See how to use snippets.
Product Update Product updates from November 2018 Improved usability and a more flexible deployment solution are some of the latest features added across the latest sprint. See what's new on the platform!
Product Update Product updates from October 2018 Major redesigns, an updated confusion matrix and a new search & filter function. Learn about the new functionalities
Tutorial Create your own house price valuation model See how you can solve common regression problems using multiple sets of input data, with deep learning
Product Update Product updates from September 2018 Usability and flexibility – these were the focus areas during the September sprints. See the improvements made
Tutorial Classifying images of clothing using CNN snippets Find out how to build and train a model for solving typical classification problems, predicting what type of clothing a specific image depicts
Tutorial Classify handwritten numbers with deep learning The MNIST classification problem is the “Hello world” of deep learning. See how you can make a real world AI web-service out of the MNIST dataset