Deeplearning | Vienna Data Science Group

Pie & AI Vienna – Why You Should Start Using AI-generated Fake Data

Mon, 12 Oct 2020 19:00:00 +0000

Welcome to our fourth online Pie & AI event!

Pie & AI is a series of deeplearning.ai meetups independently hosted by community groups. This event is hosted by the Vienna Data Science Group.

There are a few steps to complete registration, please carefully follow the next steps:

Note

(1) In Addition to RSVPing here, make sure you also register for the Webinar through this link: https://event.webinarjam.com/channel/4th-PieAI-Vienna Access to the meetup stream will be provided via email upon WebinarJam registration.

(2) Please complete your registration on the deeplearning.ai signup form here: https://forms.gle/gowTrXDxE2PUtjkZ6

After the event, we will provide a limited course promo code for attendees who sign up through the form and complete a post-event survey sent by deeplearning.ai after the event. The code is for 50% off first-month subscription to any of deeplearning.ai’s courses on Coursera.

DESCRIPTION

Why You Should Start Using AI-generated Fake Data

Up to 75% of data stored in enterprises is estimated to sit unused. Nonetheless, synthetic data generation is one of the fastest growing fields in AI. Why would anyone want to create more data if they aren’t using what they already have? In this talk, we will explore how synthetic data generation can help leverage more of today’s available data. Privacy concerns are one of the most common factors limiting data usage and one for which synthetic data provide a unique solution. In addition, synthetic data can also help counteract imbalanced and biased data. Using practical examples, we will showcase what can already be achieved with today’s available methods. Finally, we will explore tools available to explore the field and gain insights on the potential and challenges involved.

SPEAKER

Klaudius Kalcher is Co-Founder and Chief Data Scientist at MOSTLY AI, a software technology company that provides synthetic data solutions to enterprises in multiple industries. His focus is on measuring and improving the utility and privacy of synthetic data, as well as exploring how synthetic data can improve the experience of working with data.

https://www.linkedin.com/in/klaudiuskalcher/https://mostly.ai/

AGENDA

17:00 – Introduction and Greeting video by Andrew Ng

17:15 – Main Talk

17:45 – Q&A

Pie & AI: Vienna – Deep Learning in Algorithmic Trading

Fri, 17 Jul 2020 17:00:00 +0000

Download Slides

Hi,

Welcome to our second online Pie & AI Event!

Pie & AI is a series of deeplearning.ai meetups independently hosted by community groups. This event is hosted by the Vienna Data Science Group.

There are a few steps to complete registration, please carefully follow the next steps:

Note

(1) In Addition to RSVPing here, make sure you also register for the Webinar through this link: https://event.webinarjam.com/channel/VDSG-PiaAI-Vienna Access to the meetup stream will be provided via email upon WebinarJam registration.

(2) Please complete your registration on the deeplearning.ai signup form here: https://docs.google.com/forms/d/e/1FAIpQLSfO_6MQv0B95fJjGwgKGKQCvUtoeY4JEk7LofZE8qGqdBxyKQ/viewform .

DESCRIPTION

Deep Learning in Algorithmic Trading – Lessons Learned in the Real World

This talk provides a critical view on employing machine learning / deep learning methods in algorithmic trading. We highlight the particular challenges that we meet in this domain along with approaches to tackle some of these challenges in practice. Even though experience has shown that algorithmic trading using advanced machine learning can be successful, the crucial issue remains that predictive patterns utilizing market inefficiencies quickly become void as soon as competing market participants use them too. The conclusion is that the crucial advantage is – and has always been – to know more and to be faster than competitors.

OUR SPEAKER

Dr. Ulrich Bodenhofer

MSc (applied math, Johannes Kepler University, Linz, Austria, 1996) PhD (applied math, Johannes Kepler University, Linz, Austria, 1998) Since June 2018: Chief Artificial Intelligence Officer at QUOMATIC.AI (Linz, Austria)

https://www.linkedin.com/in/ulrichbodenhofer/ http://ulrich.bodenhofer.com/ https://www.quomatic.ai/

AGENDA

17:00 – Introduction and Greeting video by Andrew Ng

17:15 – Main Talk

17:45 – Q&A

Pie & AI: Vienna – Continuous-time recurrent neural networks

Mon, 08 Jun 2020 19:00:00 +0000

Hi,

Welcome to our first online Pie & AI Event!

Pie & AI is a series of deeplearning.ai meetups independently hosted by community groups. This event is hosted by the Vienna Data Science Group.

There are a few steps to complete registration, please carefully follow the next steps:

Note

(1) In Addition to RSVPing here, make sure you also register for the Webinar through this link: https://event.webinarjam.com/register/80/lxq5yb6z Access to the meetup stream will be provided via email upon WebinarJam registration.

(2) Please complete your registration on the deeplearning.ai signup form here: https://docs.google.com/forms/d/e/1FAIpQLSfO_6MQv0B95fJjGwgKGKQCvUtoeY4JEk7LofZE8qGqdBxyKQ/viewform .

DESCRIPTION

State-of-the-art time-series prediction with continuous-time recurrent neural networks.

Neural networks with continuous-time hidden state representations have become unprecedentedly popular within the machine learning community. This is due to their strong approximation capability in modeling time-series, their adaptive computation modality, their memory and parameter efficiency. In this talk Ramin will discuss how this family of neural networks work and why they realize attractive degrees of generalizability across different application domains.

OUR SPEAKER

Ramin Hasani, PhD, Machine Learning Scientist at TU Wien, expert in robotics, including previously being a scholar MIT CSAL, presents technical aspects of continuous-time neural networks.

https://www.linkedin.com/in/raminhasani/ https://repositum.tuwien.ac.at/obvutwhs/download/pdf/4937341

AGENDA

17:00 – Introduction and Greeting video by Andrew Ng

17:15 – Main Talk

17:45 – Q&A