Name: Deep Dive into Tensorflow
Start: 2016-07-20T18:30:00+02:00
End: 2016-07-20T21:30:00+02:00
Location: windeln.de AG

Due to security concerns we need the First and Last name - as on your government issued ID registered using EVENTBRITE.COM (https://www.eventbrite.com/e/munich-meetup-deep-dive-into-tensorflow-tickets-26422317864)

Many thanks to the Tensorflow meetup sponsors!

windeln.de (http://windeln.de/) for hosting and sponsoring beverages for the Tensorflow meetup,

Cape Analytics (https://www.capeanalytics.com/) for sponsoring food for the meetup

Agenda:

6:30 - Doors open. Networking. Members meet each other. Pizza and beer

7:00 - Time series classification using Deep Learning and TensorFlow by Andreas Pawlik (https://de.linkedin.com/in/andreaspawlik)

7:30 - Q&A break.

7: 50- Intro to the distributed version of TensorFlow (TensorFlow with big data on a cluster of computers) by Miha Pelko (https://de.linkedin.com/in/mihapelko)

8:20 - Q&A break.

8:40 - Wrap-up.

Detailed agenda:

http://photos4.meetupstatic.com/photos/event/7/e/e/3/600_452312483.jpeg

Time series classification using Deep Learning and TensorFlow by Andreas Pawlik (https://de.linkedin.com/in/andreaspawlik)

Abstract:

The classification of time series is a core task in data science, yet it remains challenging. Triggered by the recent success of Deep Learning in classifying images, I will review and explore the potential of Deep Learning technologies and TensorFlow for the classification of time series.

Bio:
Andreas Pawlik is a data scientist using big data technologies with a focus on the automotive industry. He discovered his interest in delivering data-driven solutions as researcher in astrophysics, where he developed and used supercomputer simulations to investigate the formation of galaxies.

http://photos4.meetupstatic.com/photos/event/7/e/c/a/600_452312458.jpeg

Intro to the distributed version of TensorFlow (TensorFlow with big data on a cluster of computers) by Miha Pelko (https://de.linkedin.com/in/mihapelko)

Abstract:

Distributed deep learning lets you train bigger models and lets you train them faster. Since March it can be done using Tensorflow natively. I will present different ways to distribute the training and do a quick run-through about how to do it in Tensorflow.

Bio:

Miha Pelko is a data scientist specialised in the field of big data in the automotive industry. Formerly he was a researcher in the field of computational neuroscience, which means he has a special affinity to deep neural networks.

Both Andreas and Miha work as data scientists at NorCom in Munich, where they combine Big Data technologies and Machine Learning techniques to help customers solve problems in the automotive industry, with applications to autonomous driving, information search and retrieval, predictive maintenance, and others.

In this context Andreas and Miha are exploring TensorFlow as one of several deep learning frameworks and would love to share and discuss our experiences with a broader audience.

Due to security concerns we need the First and Last name - as on your government issued ID registered using EVENTBRITE.COM (https://www.eventbrite.com/e/munich-meetup-deep-dive-into-tensorflow-tickets-26422317864)

Natalia Usenia

AI Performance Engineering Meetup (Munich2)

Technology

Deep Learning

Artificial Intelligence

Neural Networks

TensorFlow

Artificial Intelligence Applications

Apache Spark

Data Analytics

Kubernetes

Data Science

Natural Language Processing

Machine Learning

PyTorch

CUDA: Compute Unified Device Architecture

Deep Dive into Tensorflow

windeln.de AG

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AI Performance Engineering Meetup (Munich2)

Deep Dive into Tensorflow

AI Performance Engineering Meetup (Munich2)

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