PyLadies Dublin Nov Meetup @ Optum

We are delighted to have Optum hosting and providing food for our meetup this month.

PLEASE UPDATE YOUR RSVP IF YOU CANNOT ATTEND

If you have any announcements, please add them to https://cryptpad.fr/pad/#/2/pad/edit/UYov5AeDhBXfKtro2lNXBQcV/

Talk 1: Playing with Food-Data : Predicting your next meal !!

Description:
Food choices are personal and complex and have a significant impact on our long-term health and quality of life. By helping users to make informed and satisfying decisions, Recommender Systems (RS) have the potential to support users in making healthier food choices. Intelligent users-modeling is a key challenge in achieving this potential. This paper investigates Ensemble Topic Modelling (EnsTM) based Feature Identification techniques for efficient user-modeling and recipe recommendation. It builds on findings in EnsTM to propose a reduced data representation format and a smart user-modeling strategy that makes capturing user-preference fast, efficient and interactive. This approach enables personalization, even in a cold-start scenario. This paper proposes two different EnsTM based and one Hybrid EnsTM based recommenders. We compared all three EnsTM based variations through a user study with 48 participants, using a large-scale,real-world corpus of 230,876 recipes, and compare against a conventional Content Based (CB) approach. EnsTM based recommenders performed significantly better than the CB approach. Besides acknowledging multi-domain contents such as taste, demographics and cost, our proposed approach also considers user’s nutritional preference and assists them finding recipes under diverse nutritional categories. Furthermore, it provides excellent coverage and enables implicit understanding of user’s food practices. Subsequent analysis also exposed correlation between certain features and a healthier lifestyle.

About Mansura A. Khan: PhD student in UCD, School of Computer Science. Her research interest are Recommender Algorithms, Recommendation System Design, User Modelling , Health aware Recommendation , Personalisation, Human Compute Interaction.

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Talk 2: A deep learning approach to speech recognition of spoken words for regulatory compliance

Description: Regulatory compliance for auditory environments is a fresh domain. The presented work attempts to classify the spoken names from the raw audio files using a deep learning approach.

About Ebad Ali:
I am a data consultant at Clear Strategy and CTO at Staypal. I have a masters in Data Analytics and bachelors in Computer Science. I am independently researching in audio processing and love jiu jitsu. https://www.linkedin.com/in/ebadalie

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Talk 3: What's new in Python 3.8
A quick lighting talk by Michael Twomey.

If you want to demo or give a lightning talk on the night, let me know before I do the announcements.

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CALL FOR SPEAKERS
Interested in speaking at our upcoming meetups, please submit talk details to: https://pyladiesdublin.typeform.com/to/Rr6hVJ

CALL FOR SPONSORS
Interested in hosting us? Drop us an email and let's have a chat.

QUESTIONS Email dublin@pyladies.com.

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FAQ

Q. I'm not female, is it ok for me to attend?
A. Yes, PyLadies Dublin events are open to everyone at all levels.

Q. What do I need to bring?
A. Bring your laptop (and don't forget your charger).

Q. Will there be food?
A. Yes, and thanks to Optum for providing us food.

Q. What do you do at PyLadies Dublin Meetups?
A. We have short (or long talks), demos, folks working on their own projects, ask questions on Python-related topics, work on projects together or generally chit-chat and meet like-minded people.

Q. Do you have a Code of Conduct?
A. Yes (but we will need to find an alternative place for it, it's not easy to find on meetup) - https://www.meetup.com/PyLadiesDublin/pages/12625412/Code_of_Conduct/

IF YOU CANNOT MAKE IT, PLEASE UPDATE YOUR RSVP