Name: Deep Learning
Start: 2019-05-21T18:30:00+02:00
End: 2019-05-21T21:30:00+02:00
Location: quintly

CAIML #7 will happen on May 21, 2019. This time we are doing a joint event together with the Facebook Developer Circle Cologne (https://www.facebook.com/groups/DevCCologne/). The topic of CAIML #7 will be Deep Learning.

Agenda (tentative):

18:30 - Doors open

19:00 - Welcome & Intro

19:15 - Immanuel Weber (PhD-Student at University of Applied Sciences Koblenz, https://www.linkedin.com/in/immanuel-weber-8b5822182/): Deep Learning - A hands-on introduction to image classification

Deep Learning is for some the Holy Grail and for others the root of all (future) evil. Besides the hype and buzzwords, it is a highly useful way of solving problems in many areas, which were difficult or impossible to solve in the past. Originally having gained traction mainly in computer vision, it is currently gaining a lot of momentum in text and language processing, but also in structural data problems. We will take a look at the core principals of neural networks, important architectures and some tricks of the trade. We will answer questions such as how neural networks are trained and what makes them deep. After a brief look at current solutions and milestones, we will dive into the implementation of an image classifier using state of the art tools. The use of pytorch in conjunction with a high-level library like fast.ai allows us to quickly test ideas and implement prototypes. The common assumption that deep learning requires huge amounts of hardware and/or time is generally not true and allows us to see results within the talk.

19:45 - Break with drinks and food

20:15 - Dominik Seisser (NLP Expert at Cognigy, https://www.linkedin.com/in/seisser/): Should you be afraid of Transformers? Learn about latest breakthroughs in NLP and how you build a menacing AI yourself.

We look at the latest advances in language models, a small step forward in machine learning towards our quest for more general artificial intelligence. Powerful language models based on the "Transformer" deep learning architecture have set new benchmarks in Natural Language Processing (NLP). The release of the "BERT" model has been described as the ImageNet moment of Computer Vision for NLP - with highly successful transfer learning where a pre-trained model can be fine-tuned for a wide range of tasks. The new models have generated huge controversy. We have a first precedence with OpenAI's GPT2 model where a research group decided to not release their work to the community out of concern for malicious applications of AI technology. Is current AI tech dangerous? What does withholding of models mean for open research and startups in a field dominated by a small number of giant monopolies? For now, we show how you can tackle your next NLP project utilizing the power of new language models. They are also a beast in production. We look at paths to take these advances to production and get those menacing world-class NLP results.

20:45 - Closing & Networking

Make sure to also check https://deep-learning-ai-devc.splashthat.com/ for more information.

Fabian Hadiji

Cologne AI and Machine Learning Meetup

Technology

Data Analytics

Artificial Intelligence

Big Data

Predictive Analytics

Data Mining

Data Science

Machine Learning

Deep Learning

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Cologne AI and Machine Learning Meetup

Deep Learning

Cologne AI and Machine Learning Meetup

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