Online Course – Machine Learning in Industry 4.0

09. September 2022, 09:00 until 23. September 2022 16:00

Online Course – Machine Learning in Industry 4.0

Other

Machine Learning in Industry 4.0 is a 5-days interactive online training, especially designed for professionals (such as engineers and other technical professionals, as well as students) interested in the basic theory of Machine Learning (ML) (for example, theory on the ML landscape, support vector machines, decision trees etc.), but who would also like to learn about Deep Learning and its practical application with solving a classification or regression model problem.

By the end of the training the participants will be able to understand the basic concepts of Machine Learning and its application to the Manufacturing and Industry context. The training is interactive with application of real case examples across all days.

Program:

Block 1:
09 September 2022

Theory, basic ideas of Machine Learning (ML) & ML landscape
Support Vector Machines, Decision Trees
Random Forests and Ensemble Learning

Block 2:
12 September 2022

Theory and basic ideas of Neural Networks (NN) & Deep Learning (DL)
Quick tour of TensorFlow and Keras
Solving a regression problem
MNIST dataset: The Hello World of DL

19 September 2022

Convolutional Neural Networks (CNNs)
Manufacturing/industry-related examples
Transfer learning on CNNs
Manufacturing/industry-related example

21 September 2022

Convolutional Neural Networks (CNNs)
Manufacturing/industry-related examples
Transfer learning on CNNs
Manufacturing/industry-related example

Block 3:
23 September 2022

Wrap up, repetition & outlook
High-Performance Computing (HPC)
Training a NN on an HPC cluster
Means and methods of improving performance

Prerequisites:

The participants are expected to have at least basic programming skills in Python.

Hands-on Labs:

Participants will use their own laptop or workstation to do the hands-on exercises. We will use Anaconda (https://www.anaconda.com) and more detailed instructions how to download the software and setup the environment will be provided to the participants before the course starts. In addition, all participants will get a temporary training user on the VSC for the last course day, any up-to-date browser will be enough to connect to the VSC Jupyterhub and train a neural network on the HPC facilities of the Vienna Scientific Cluster.

Course Material:

The course material will be available for registered attendees at course start.

Lecturers:

Simeon Harrison and Claudia Blaas-Schenner (EuroCC Austria and VSC Research Center, TU Wien), Philipp Danninger (EuroCC Austria and Know-Center).

Language: English

Date, Time, and Location:

09.+12.+19.+21.+23. 09. 2022, 09:00 - 16:00 CEST, LIVE ONLINE COURSE (using Zoom)

Prices and Eligibility:

Price for the full course with certificate of attendance:
360 EUR/person (including VAT)

FREE info webinar before the start of the course:

30 August 2022, 16:00 - 17:00. Register here: www.eventbrite.com/e/machine-learning-in-industry-40-online-training-info-webinar-tickets-403405315157

Calendar entry

Event location

TU Wien
Zoom, Online

Organiser

EIT Manufacturing CLC East in cooperation with EuroCC Austria, Vienna Scientific Cluster (VSC), and Know-Center.
Simeon Harrison
training-eurocc@vsc.ac.at

More Information

https://vsc.ac.at/training/2022/ML_Industry40/

Public

Yes

Entrance fee

Yes

Registration required

Yes

Registration via EIT Manufacturing CLC East: https://eitmanufacturing-east.eu/product/machine-learning-in-industry-4-0/ , opens an external URL in a new window

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SimpleSAMLAuthToken	This is needed to distinguish between the sessions of the logged-in users.	session	HTTP	Login TU Wien
fe_typo_user	Is needed so that in case of a Typo3 frontend login the session ID is recognized to grant access to protected areas.	session	HTTP	Homepage TU Wien
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__SECURE-APISID	Is needed to profile the interests of website visitors in order to display relevant and personalized advertising through retargeting.	8 months	HTTP	Google
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test_cookie	Is set as a test to check whether the browser allows cookies to be set. Does not contain any identification features.	15 minutes	HTTP	Google
VISITOR_INFO1_LIVE	Is needed by YouTube to store user settings and to calculate user bandwidth.	6 months	HTTP	Youtube
facebook	Is used to Enable ad delivery or retargeting	90 days	HTTP	Meta (Facebook)
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fbm	Is needed to store account data (marketing/tracking).	1 year	HTTP	Meta (Facebook)
xs	Is needed to store a unique session ID (marketing/tracking).	1 year	HTTP	Meta (Facebook)
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fr	Is needed to serve ads and measure and improve their relevance.	3 months	HTTP	Meta (Facebook)
act	Is needed to store logged in users (marketing/tracking).	90 days	HTTP	Meta (Facebook)
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datr	Is needed to identify the browser for security and website integrity purposes, including account recovery and identification of potentially compromised accounts.	2 years	HTTP	Meta (Facebook)
dpr	Is used for analysis purposes. Technical parameters are logged (e.g. aspect ratio and dimensions of the screen) so that Facebook apps can be displayed correctly.	1 week	HTTP	Meta (Facebook)
sb	Is needed to store browser details and security information of the Facebook account.	2 years	HTTP	Meta (Facebook)
dbln	Is needed to store browser details and security information of the Facebook account.	2 years	HTTP	Meta (Facebook)
spin	Is needed for promotional purposes and social campaign reporting.	session	HTTP	Meta (Facebook)
presence	Contains the "chat" status of logged in users.	1 month	HTTP	Meta (Facebook)
cppo	Is needed for statistical purposes.	90 days	HTTP	Meta (Facebook)
locale	Is needed to save the language settings.	session	HTTP	Meta (Facebook)
pl	Required for Facebook Pixel.	2 years	HTTP	Meta (Facebook)
lu	Required for Facebook Pixel.	2 years	HTTP	Meta (Facebook)
c_user	Required for Facebook Pixel.	3 months	HTTP	Meta (Facebook)
bcookie	Is needed to store browser data (marketing/tracking).	2 years	HTTP	LinkedIn
li_oatml	Is needed to identify LinkedIn members outside of LinkedIn for advertising and analytics purposes.	1 month	HTTP	LinkedIn
BizographicsOptOut	Is needed to save privacy settings.	10 years	HTTP	LinkedIn
li_sugr	Is needed to store browser data (marketing/tracking).	3 months	HTTP	LinkedIn
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linkedin_oauth_	Is needed to provide cross-page functionality.	session	HTTP	LinkedIn
lidc	Is needed to store performed actions on the website (marketing/tracking).	1 day	HTTP	LinkedIn
bscookie	Is needed to store performed actions on the website (marketing/tracking).	2 years	HTTP	LinkedIn
X-LI-IDC	Is needed to provide cross-page functionality (marketing/tracking).	session	HTTP	LinkedIn
AnalyticsSyncHistory	Stores the time when the user was synchronized with the "lms_analytics" cookie.	30 days	HTTP	LinkedIn
lms_ads	Is needed to identify LinkedIn members outside of LinkedIn.	30 days	HTTP	LinkedIn
lms_analytics	Is needed to identify LinkedIn members for analytics purposes.	30 days	HTTP	LinkedIn
li_fat_id	Required for indirect member identification used for conversion tracking, retargeting and analytics.	30 days	HTTP	LinkedIn
U	Is needed to identify the browser.	3 months	HTTP	LinkedIn
_guid	Is needed to identify a LinkedIn member for advertising via Google Ads.	90 days	HTTP	LinkedIn

Research Events

Online Course – Machine Learning in Industry 4.0