Modulos AutoML allows building state-of-the-art machine learning solutions in a fully automated manner. To further illustrate this, we’ll share a use case where we performed an image classification experiment. Modulos AutoML handles image data, tabular data, as well as a combination of both.
Our latest version of Modulos AutoML is out. With this version, we are giving you a completely redefined ML workflow creation process.
Ever wondered how decision trees and random forests work and what problems they can solve? This blog is here to answer your questions!
Yale astronomy researcher Aritra Ghosh spent more than three months manually building a deep learning classifier for galaxy images. When experimenting with Modulos AutoML, he was able to automatically build a similar performance deep learning classifier with two weeks of computational time.
Our latest version of Modulos AutoML is out: v.0.3.5. With this version, we are adding major speed improvements to the assessor, which determines if a neural network has finished training. We are also preparing a new and improved workflow creation, which we are excited to share with our customers soon. We are including a sneak peek here.
In this blog post, Modulos Sales Manager Florian Marty describes his experience using AutoML to solve a current scientific challenge using his biology domain knowledge.
Modulos CEO Kevin Schawinski was 2021’s first guest on the “Datenbusiness-Podcast”. This German-language podcast hosted by Dr. Bernard Sonnenschein covers topics all around getting value from data, data science and business applications of data. Previous guests include executives from SAP, Lufthansa and Allianz, as well as leading German academics.
The Swiss government has published its guidelines for the use of AI within the federal government. We at Modulos support this effort.
It’s our ambition for Automated Machine Learning that building machine learning models should be an easy task where most of the technical heavy lifting is done by the platform. We therefore need to design a user interface which facilitates this. We spoke to Evangelia “Litsa” Mitsopoulou who joined Modulos in October 2019 to work on all aspects of the user interface.
The Institute for Astrophysics at PUC in Chile is using Modulos AutoML to support their research. Kevin Schawinski spoke with Professor Ezequiel Treister about how automated machine learning is enabling cutting edge astronomy research and training students in using machine learning.