PyData June @ babbel

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PyData Berlin June meetup is hosted by babbel. Doors open at 18:45 and the talks are going to start shortly after seven. Food and Drinks are provided generously provided by babbel.

We have 2 speakers scheduled for the evening: Daniel Davis and Amit Kushwaha as well as three lightning talks.


Using numba along cooperative inheritance to efficiently execute composable simulations by Daniel Davis

The talk shows how simcompyl, a discret-time simulation library, applies
numba's jit-compilation for blazing fast executions while keeping the
complete flexibility of python, including cooperative inheritance and
debugging capabilities.

Daniel is a Data Scientist working at Gameduell, helping to improve their gaming community site and mobile games experience. He has a strong background in programming and not only enjoys data analysis and model building in python, but also implementing some bigger projects. You may also know him from one of Berlins hackerspaces or from a c3 event, but currently he is quite busy setting up him farm in Havelland.


Adversarial Machine Learning: Cybersecurity Perspective by Amit Kushwaha

Security and Privacy issues need no introduction. But how exactly is this affecting the field of Machine Learning? This is what this talk will cover. We first expose the attack surface of systems deploying machine learning. We then describe how an attacker may force models to make wrong predictions with very little information about the victim. One such attack can be biometric recognition where fake biometric traits may be exploited to impersonate a legitimate user. We demonstrate that these attacks are practical against existing machine learning as a service platform. Towards the end, we will discuss current research to defend models from such attacks.

Amit is a Python Backend Engineer in the Pricing and Forecasting Team of Zalando SE. He is currently working on Optimal Discount Recommendation on Large Scale. He worked earlier as a Machine Learning Engineer in Zomato. His major areas of interests are Deep Learning, Recommendation Systems, Natural Language Processing and Data Engineering. He is also an Open Source Enthusiast. He is proficient in Python and has worked with the Tensorflow, Keras, Pyspark, Airflow, Luigi and Pandas libraries to name a few. He dreams to pursue Artificial Intelligence as an independent researcher in future.