Datum:26.3.2020 (čtvrtek), registrace od 8:30
Místo:Best Western Premier Hotel International Brno, Brno, Česká repulika
Přednášející:Loren Shure (MathWorks), Alessandro Tarchini (MathWorks)
Využijte mimořádnou příležitost k seznámení se s paní Loren Shure
, jednou z nejvýraznějších osobností společnosti MathWorks
, která přispěla rozhodující měrou k vývoji systému MATLAB
a jeho jazyka. V rámci její návštěvy České republiky pořádáme dvě setkání s uživateli formou tohoto dopoledního semináře a odpoledního „Master Classu
Na semináři vystoupí i pan Alessandro Tarchini
, který se ve společnosti MathWorks zaměřuje na využití programu MATLAB na evropských univerzitách a reprezentuje MathWorks v mezinárodních společnostech pro rozvoj technického vzdělávání jako jsou SEFI, IGIP a European Engineering Dean Council.
Current trends in Engineering Education
Alessandro Tarchini (MathWorks)
Universities around the world are revamping curriculum to cover areas like "new machines" based on the acknowledgement that traditional systems within industries are now extending to include more and that disciplinary boundaries have blurred.
Facing industry driven mega-trends like electrical activation, inter-system communication or data science and AI, universities have to adapt content and format to the increasing demand for cross-disciplinary approach to problem-solving.
Engineering software tools have become an essential part of "treating engineering students like engineers" not only because as they graduate and integrate into the workforce they must be familiar with these techniques, but also because they help universities to deal with issues like attractiveness of engineering education, retention and employability of students.
Let's have a look at how some of the most innovative engineering universities in the world are integrating engineering software tools in their curriculum.
Demystifying deep learning: A practical approach in MATLAB
Loren Shure (MathWorks)
Deep learning, a chief driver of the AI revolution, can achieve state-of-the-art accuracy in many cognitive or perceptual tasks such as naming objects in a scene or recognizing optimal paths in an environment.
It involves assembling large data sets, creating a neural network, and training, visualizing, and evaluating different models, using specialized hardware - often requiring unique programming knowledge. These tasks are frequently even more challenging because of the complex theory behind them.
In this seminar, we’ll demonstrate new MATLAB features that simplify these tasks and eliminate the low-level programming. We’ll build and train neural networks that recognize handwriting, categorize foods, classify signals, and control machines.
Topics within this talk include the following:
- Manage large data sets (images, signals, text, etc.)
- Create, analyze, and visualize networks, and gain insight into the black box nature of deep learning models
- Automatically label ground truth or generate synthetic data
- Build or edit deep learning models with a drag-and-drop interface
- Perform classification, regression, and semantic segmentation with images or signals
- Apply reinforcement learning with deep Q networks (DQN)
- Leverage pre-trained models (e.g. GoogLeNet and ResNet) for transfer learning
- Import models from Keras-TensorFlow, Caffe, and the ONNX Model format
- Speed up network training with parallel computing on a cluster
9:00Current trends in Engineering Education
9:30Demystifying deep learning: A practical approach in MATLAB - 1. část
11:00Demystifying deep learning: A practical approach in MATLAB - 2. část
12:00Diskuse a závěr
Loren Shure, MathWorks.
Loren has worked at MathWorks for over 30 years. For the first 27 of these years, Loren co-authored several MathWorks products in addition to adding core functionality to MATLAB, including major contributions to the design of the MATLAB language. She is currently part of the Application Engineering team, enabling Loren to spend more time and energy working with customers.
For more than 10 years, traveling worldwide over half of each year, Loren delivers more than 150 technical, strategic, and vision-setting presentations yearly to audiences ranging from hands-on problem solvers through high-level executives.
Loren graduated from MIT with a B.Sc. in physics and has a Ph.D. in marine geophysics from the University of California, San Diego, Scripps Institution of Oceanography. She is a Senior Member of IEEE; and she is co-author on several patent inventions. Loren writes about MATLAB on her blog, The Art of MATLAB
Alessandro Tarchini, MathWorks.
Born in Genova in 1962, since 1982 he has worked in ICT, initially developing firmware for numeric control systems, then spending three years at the computing data center "Sergio Borgogno", developing Finance applications for the public administration.
From 1985 to 1990 Alex worked in Stratos – a company providing services to Aerospace and Defense, as a consultant to aerospace companies, representing Italy in international project teams defining and developing processes for the engine management in the civil aviation business.
In 1992, after moving to Teoresi, he expanded his interests to software systems for number crunching, modelling and simulation; since 1993 Alex has worked in favor of advanced numerical analysis techniques facilitating the adoption of MATLAB in Italy. In 2002, when the Italian operations of MathWorks Inc. were opened, he was appointed as the managing director of the new company.
After managing MathWorks Italian operations for 10 years, Alessandro moved to Educational Business and Market Development and is now helping academic organization to maximize the value of MATLAB in teaching and research.