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AutoML v.0.3.5: Assessor Speed-up and a Sneak Peek

Claudio Bruderer

Written by:
Claudio Bruderer (Product Manager at Modulos)

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.


Data Science Updates

Assessor Speed-Up

The training process phases each candidate solution passes through.

The Modulos AutoML solutions are trained iteratively. For neural networks in particular, the platform repeats this training process multiple times. This is controlled by the assessor, which decides whether the model needs to continue training for another epoch. If not, training stops and the final solution is packaged and made available to you.

In this release, we refined the assessor step. We use the median stopping rule to stop the training cycles, if the median of the validation scores stops improving. We now also take the variance of the scores into account with the goal of avoiding plateauing scores without significant improvements. These changes lead to a 10% to 70% speed-up when training neural networks (performance tested on identical machines and data, speed-ups vary depending on the ML task type). At the end of the training cycle we return the solution with the best validation score. Compared to previous Modulos AutoML versions, this allows you to generate more and better solutions within the same time frame.

Descriptions of Objectives

Redesigned descriptions of the objective selection in the workflow creation.

The configuration of the Machine Learning task – the workflow – by you as the domain expert is one of the crucial steps when tackling your use case with the AutoML process. During the workflow creation it is important to choose the appropriate objective, the measure which AutoML optimizes for. We standardized and expanded the descriptions of these objectives in the workflow creation to follow a clear design.


Platform Updates

Sneak Peek: Fully Redesigned Workflow Creation

An impression of the new workflow creation to be released soon.

We are happy to give you a sneak peek into what we are currently working on and are looking forward to sharing with you. We are redefining the entire workflow creation process. Besides giving it a fresh and sleek look, it will allow for more flexibility and dynamicity when configuring a Machine Learning task. With this new generation of the workflow creation, we will be able to provide you with even more exciting features in the near future. So, stay tuned!


Other Improvements and Bug Fixes

Plots in the README for solutions giving insights into the performance of a neural network on validation data.

We additionally made a range of fixes and improvements to AutoML, which include:

  • Refined the Kernel Density plot in the README for trained solutions for regression tasks. This figure allows you to visually assess a solution’s performance on the validation data. The scaling of the color map has been polished and we have expanded the range of datasets, for which it is applicable.
  • Updated the README to also include detailed instructions on how to update the AutoML platform to the latest version.
  • Made the F1 Score objective for binary classification more robust to accept a wider range of data.

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Jérôme Fischer

Sales Development

“The only way to do great work, is to love what you do.” – Steve Jobs

Jérome Fischer is an expert on Sales. Apart from the successful build up of several companies like the Ad Interim Sales GmbH and the Sales4IT GmbH, he passes on his experience in various Sales and Marketing coachings. Jérome now supports Modulos in establishing the first contact with our customers.

In his free time, Mr. Fischer is an ambitious athlete with numerous awards.

Dominic Stark

Dominic Stark

Data Scientist

Code quality correlates with food quality.

Dominic Stark studied physics at ETH Zürich. The transition of his career path to Data Science began when he was analyzing UV images of galaxies. Together with Kevin Schawinski an Ce Zhang, he worked on applying the latest advances of deep learning research to his problem. It turned out that the method itself was at least as interesting as the problem they designed it for. After publishing the results, his research project was about using Reinforcement Learning to develop novel ideas for data acquisition in astronomy. As a Data Scientist at Modulos, he keeps on solving problems, that require new ideas and technologies.

Kevin Schawinski

Kevin Schawinski

CEO / Co-Founder

Running a startup is super relaxing, right?

While a Ph.D student, he co-founded the Galaxy Zoo citizen science project involving more than a million members of the public in scientific research because machines weren’t quite good enough yet to go map the cosmos and classify galaxies. He stayed in Oxford as the Henry Skynner Junior Research fellow at Balliol College before moving to Yale as a NASA Einstein Fellow. In 2012, he started the galaxy and black hole research group at ETH Zurich as an assistant professor and began a close collaboration with Ce Zhang from computer science to work on the space.ml project. He is now the CEO of Modulos.

Ce Zhang

Ce Zhang

Co-Founder

Random is best.

He believes that by making data—along with the processing of data—easily accessible to non-computer scientists, we have the potential to make the world a better place. His current research focuses on building data systems to support machine learning and help facilitate other sciences. Before joining ETH, Ce was advised by Christopher Ré. He finished his PhD round-tripping between the University of Wisconsin-Madison and Stanford University, and spent another year as a postdoctoral researcher at Stanford. His PhD work produced DeepDive, a trained data system for automatic knowledge-base construction. He participated in the research efforts that won the SIGMOD Best Paper Award (2014) and SIGMOD Research Highlight Award (2015), and was featured in special issues including the Science magazine (2017), the Communications of the ACM (2017), “Best of VLDB” (2015), and the Nature magazine (2015).

Alexandra Arvaniti

Alexandra Arvaniti

Operations Manager

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During the last twenty years, she worked in different roles, setting up and running PMOs, supporting the Executive Management Team or as Operations Manager for the DACH region. She loves all organizational challenges, which she can use well at Modulos, like set up and establish administrative business processes.

Rudolf Bar

Rudolf Bär

Chairman of the Advisory Board

After initially working for Dow Corning International in Zurich and Brussels (1964 to 1969), he held various management functions in the Private Banking Group Julius Baer, Zurich, lastly as CEO from 1993 to 2000 and retired from its Board of Directors in 2005. Since 2014 he has been studying at the Institute for Particle Physics and Astrophysics at the ETH, Zurich.

Marianne Chiesi

Marianne Chiesi

Administration

Marianne has worked in administration of various companies and the ETH.

Marianne Chiesi worked in the administration of various companies before taking time off to raise her children. She translated text books and literary works into Braille and joined the ETH Zurich as an administrative assistant. At ETH, she worked with professorships and researchers in many areas, including astrophysicists, particle physicists and biochemists. She now runs the administration at Modulos.

Bojan Karlaš

Bojan Karlaš

Software Engineer

Real engineers must be a little bit lazy.

After getting a bachelor’s degree in software engineering at the University of Belgrade, Serbia, Bojan spent 2 years working as a developer at Microsoft building distributed database solutions. He then went to Switzerland to pursue a computer science master’s degree at EPFL. He did his master thesis with Ce Zhang at ETH Zürich on the topic of time series forecasting, after which he joined Ce’s group as a PhD student. His industry experience also includes internships at Microsoft, Oracle and Logitech. His research interests revolve around systems and abstractions for making machine learning accessible to non-experts.

Romain Lencou

Romain Lencou

Head of Engineering

Deleted code is debugged code. (Jeff Sickel)

Romain Lencou graduated from the Grenoble Institut National Polytechnique with M.Sc in Computer Science in 2008. Growing up in France in the 90’s, he developed an enthusiasm for pop culture, technology and food. Always eager for technological challenges, Romain worked for companies like VMware, Intel and Logitech, covering various topics including cryptography, virtualization and computer vision. Bitten by the machine learning bug, he is looking forward to apply his problem solving skills in Modulos.

Dennis Turp

Dennis Turp

Data Scientist

Dennis Turp is the first employee of Modulos.

Prior to his work at Modulos he studied physics at ETH Zurich. During his Master studies he worked together with Kevin Schawinski and Ce Zhang on exploring machine learning related topics in astronomy. In these one and a half years they published three scientific papers together. Dennis Turp is currently employed as a Data Scientist. His main expertise lies in the fields of generative modeling and anomaly detection.

Michael Röthlisberger

Michael Röthlisberger

Data Scientist

Data handling with structure

He started to take an interest in Data Science and Software Development during his master’s degree. For his master thesis he worked on the image reconstruction software for a new PET detector. Michael gained some first experience in an internship for Sensirion AG. There he was part of the R&D team, which was developing a new gas sensor. The participation of a machine learning hackathon was sparking the interest of Michael in ML and he decided to pursue a career in this field. He is now exited to face new challenges with modulos and experience working in a rising start-up.

Laura Guerrini

Data Science Intern

Laura Guerrini is the first intern of Modulos.

Laura is currently finishing her Master’s in Robotics, Systems and Control at ETH. During her studies, she focused on machine learning, control theory and optimization. She joined Modulos as a Data Science Intern to put theory into practice and boost her machine learning and programming skills.

Andrei Văduva

Andrei Văduva

Software Engineer

The trendsetter geek

He focused his attention on designing Architectures of Computer Systems. During university, he gained an excellent understanding of performance optimization and scalability on architectures such as distributed systems. Having a good experience in various Computer Science fields like big data analytics and Artificial Intelligence, he did his bachelor’s thesis designing a Machine Learning algorithm for social media platforms. After graduation, he joined the investment banking industry, in London, where he gained good experience in designing and building high-quality software. Andrei moved to Switzerland to explore new perspectives and found a great challenge in the startup world. Using his passion for technology and professional experience, he brings the best practices in software engineering to Modulos.

Modulos appoints Anna Weigel as CTO

Anna Weigel

Chief Technology Officer

After acquiring Bachelor and Master degrees in Physics, Anna completed her PhD in Astrophysics in Kevin Schawinski’s group at ETH. Her work on the relationship between supermassive black holes and their host galaxies is summarized in five first-author papers. After exploring the depths of our Universe, Anna joined Modulos as the Head of Data Science. She has since been appointed the role of CTO and is now leading the overall technology development.

Claudio Bruderer

Claudio Bruderer

Product Manager

Give me coffee to function.

After obtaining a BSc and a MSc degree in physics at ETH Zurich, Claudio decided to continue his studies of the Universe as a PhD student in Prof. Refregier’s Cosmology research group. He studied the gravitational lensing effect, whereby he measured the shapes of several billions of galaxy images (mostly synthetic ones). After acquiring his PhD, Claudio then joined the consulting company AWK Group AG and worked as a project manager and associate for IT and communications projects in the logistics and mobility sectors and for the federal government. Determined to create cutting-edge IT solutions, he decided to join Modulos as a product manager.

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Christoph Golombek

Christoph Golombek

Sales Manager

Happy customers, happy Christoph – or is it the other way around?

After finishing his master studies in Energy Technology at RWTH in Germany, Christoph started his professional career as an expert and Sales Support Engineer for wind turbines in cold climates in Canada. There he started seeing the benefits of machine help in tackling data-driven challenges. Having explored the great North, his passion for cutting edge technology drove him into the machine vision sector in Switzerland, where he has worked as a fusion of Sales Engineer and Tech Support, while also acting as a Team Leader of a team of four. At Modulos, he can now focus again on bringing state-of-the-art technology to happy customers.

Florian Marty

Florian Marty

Sales Manager

Putting Science into the Art of Sales.

As a Ph.D. in Molecular Biology from the University of Zurich, Florian Marty was, like most scientists, not a big fan of sales initially. But, over the years and with growing experience in different commercial roles, he learned that there is a lot of science in what makes good salespeople. Coupled with his open mindset to learn new things and a communicative personality, Florian is fascinated to explore and test new strategies, tactics, and expert moves in sales. As a Sales Manager, he will be joining the commercial team helping to grow the customer base and make Machine Learning accessible to everyone. Fun fact, as Florian has never written a single line of code in his life.

We believe he is the perfect fit to bring across the Modulos value proposition to our customers. Do not hesitate to reach out to Florian to engage in a discussion about Modulos AutoML.