PyData Berlin July Meetup

Welcome to the July Virtual Meetup - this time cross-linked with PyData Jeddah https://www.meetup.com/PyData_Jeddah/

The talks will start at 19:00

The link to the Zoom meeting will be sent to all attendees about an hour before the meetup and there will be a YouTube live stream for those not on the zoom call.

We have two great speakers for the upcoming meetup, as well as an informative PyData break in between.

The Schedule for the evening:

Talk 1: 35 mins

Title: Quantum Machine Learning for Programmers

speaker: Dr. Maria Schuld

Abstract: Algorithms that run on quantum computers - so-called quantum circuits - underlie different laws of information processing than conventional computations. By optimizing the physical parameters of quantum circuits we can use them like neural networks, and train circuits to generalize from data. This talk highlights different aspects of such "variational quantum machine learning algorithms", including their role in the development of near-term quantum technologies, their connection to classical machine learning, and strategies of fitting the quantum model to data. The theory will be illustrated by code examples from the python-based open-source software framework "PennyLane" throughout the talk.

Bio: Maria Schuld works as a researcher for the Toronto-based quantum computing start-up Xanadu, as well as for the Big Data and Informatics Flagship of the University of KwaZulu-Natal in Durban, South Africa. She received her PhD from the University of KwaZulu-Natal in 2017 for her work on the intersection of quantum computing and machine learning, which was published as the book "Supervised Learning with Quantum Computers" (Springer, 2018, co-authored by F. Petruccione). Besides her physics background Maria has a postgraduate degree in political science, and a keen interest in the interplay of emerging technologies and society.

Talk 2: 35 mins
Title: Application of NLP in the UK rail Industry

Abstract: This talk will describe how the python NLP ecosystem has been used to help with maintenance of the UK stations lifts and escalators.
By the end of this talk, members will learn how to convert an unsupervised NLP problem to a semi-supervised one. Alongside this, parallelism with Python multithread processing will be explored on how it was used to spell check and clean 150,000 maintenance reports.
The talk will also explore when to build ML models and when to use good-old pure python for solving NLP problems

Bio: Ali Parandeh is a Chartered Engineer and Microsoft certified data scientist (MCADSA) with 5 years of engineering consulting experience in the rail industry and he is the Founder and instructor at Beginners Machine Learning Group in London. He uses data science and machine learning technologies to help transport clients make key decisions by developing data analytics and predictive solutions

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THE SHORT VERSION

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