PyData Hamburg May Meetup

Hey PyData Hamburg community,

How is it going? We hope you are doing great today, and we would like to invite you for our May meetup. Yay! :-)

What you need to know to participate in remote meetups:

• Our virtual room capacity is limited to 300 attendees. So RSVP on meetup.com please and do take the time to cancel if you cannot join.
• The link to the Zoom meeting will be displayed to you on meetup.com when you RSVP. Please do not share it.
• You need to be logged in with a free Zoom account - this is an anti-troll measure.
• Please check in a few minutes before the event starts so we can support you with questions about access.

Take care, stay healthy and see you soon.
Your Pydata Hamburg crew

# (Talk 1) Smriti Singh: NLP for Hate-speech detection: Why does it matter and what can we do?

Talk Description:
In a world where social media is becoming one of the most prominent
platforms for social impact, there has been a surge in hate speech,
cyberbullying and abusive speech on social media. Consequently, there
has been an increase in research that aims to automate the detection
of offensive content. In this talk, I’ll cover the following topics:
1. What are the most common different forms of hate-speech that we see
on social media today?
2. Why is detecting hate-speech important?
3. NLP and Machine Learning for Hate speech detection: An overview
4. NLP and Deep Learning for hate speech detection: An overview
5. NLP and Machine Learning vs Deep Learning: When to use which?
6. How can we help? Examples of open source frameworks and public
datasets

About Smriti

Smriti Singh is an NLP Research Intern at Meedan and also a Research Assistant at The Centre for Artificial and Machine Intelligence, Manipal and an upcoming Data Science Intern at UnitedHealth Group Optum . She is currently studying Information Technology at Manipal Institute of Technology, India.

# (Talk 2) Dr. Paul Elvers: Getting Started with MLOps: Tools and Best Practices for Production-Ready Machine Learning Systems

Talk description:
MLOps (ML + DevOps) describes the necessary practices & techniques for maintaining machine learning (ML) models in production. Thinking about machine learning from an MLOps-perspective shifts the focus of attention towards how models behave “in the wild” rather than optimising the model performance on a recognised training data set (e.g. MNIST) in ml-research. Thinking of ML from an MLOps-perspective is crucial for a successful use of machine learning in any business. I present the core concepts of MLOps and share insights about useful tools and technologies for building a minimal working ML system.

About Dr. Paul Elvers

Dr. Paul Elvers is Head of AI/Data Science at Datadrivers, an IT Consulting Company in Hamburg. He graduated in Systematic Musicology & worked as a Research Fellow at the Max-Planck-Institute for empirical Aesthetics.

PyData is a community for developers and users of open-source data tools. PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. The PyData Code of Conduct governs this meetup.