What we're about

All hands-on meetups around hacking traditional machine learning down to creating some intelligent agents and self-driving models.

Who should join: We are open to anybody who is interested in Machine Learning or Data Science from really new, but already passionate up to experienced folks, who would like to play around side projects.

Why members should join: To learn, share, and have fun doing so.

What members can expect: Monthly meeting with knowledge sharing on related topics

Do not miss out updates on twitter - https://twitter.com/hack_ai and join Munich ML community on Slack channel https://ai-hack-inviter.herokuapp.com/

Upcoming events (1)

#20 - 2019.01 - ML as a design material; TF2.0; Tensorflow.js

🆂🅻🅾🆃 #1: Machine Learning as a design material - Agnieszka Billewicz In the recent years more and more artists and designers are getting involved in the field of Machine Learning. But how exactly are the creatives experimenting with ML? And what role can ML have in the design process? In this talk we will look at examples of experiments, projects and approaches of Human-Centred Machine Learning to see how ML algorithms can be used to create new types of interactions, engage stakeholders and re-imagine the relationship between human and technology. Agnieszka Billewicz is an interaction designer from Poland, who likes to imagine how people’s relationship with technology could be different, including more playful. Her ML explorations in form of co-design sessions, sketches and prototypes has formed two Master’s thesis works defended at Malmö University in Sweden, and published design research. Her work has been presented at international events conferences and festival, such as CHI’18 or Push Conference. 🆂🅻🅾🆃 #2: TBA 🆂🅻🅾🆃 #3: Client-side Artificial Intelligence in JavaScript using Tensorflow.js Tensorflow.js can be used to develop machine learning models that run on nodejs or in the browser. Existing models can also be reused or retrained. Using WebGL, the framework provides vendor independent support for hardware acceleration and can even outperform CPU-bound training. In an example I will demonstrate how to use the low-level APIs and how to build a gesture classifier gathering training data from the webcam. Mathias Burger is enthusiastic about open source software and always interested in the latest trends in IT, especially in computer vision. He is Senior Consultant at TNG Technology GmbH and is currently working on a defect detection system in the aerospace industry. For deep learning, he likes to use Tensorflow, Keras, Pytorch and fast.ai, depending on the use case. Furthermore he is the author of pgimp, a python3 library to interact with GIMP conveniently. We are looking for speakers and sponsors! As always, we are super happy to have you with a lightning talk on your small or big successes, open source projects or just something amazing you would like to share. Do not miss out updates on twitter - https://twitter.com/hack_ai and join Munich ML community on Slack channel https://ai-hack-inviter.herokuapp.com/

Past events (20)

#19 - 2018.11 - Complex chatbot dialog flows; Document scanning on mobile

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