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Kicking off the year with our first meetup, we are continuing the tradition of showcasing real-world serverless ML projects built by KTH students!

From forecasting cross-border energy flows to predicting transit delays with live weather data, these projects highlight how fully serverless ML systems can tackle real-world challenges.

Agenda:

17:30 - 18:00: Doors open 18:00 - 18:20: Welcome - Intro 18:20 - 18:35: E-FlowCast – Forecasting Cross-Border Energy with Serverless ML 18:35 - 18:50: Real-time weather-based transit delay forecasting 18:50 - 19:20: Pizza & Beers 19:20 - 19:35: The Ultimate 1Million Movies Dataset 19:35 - 19:55: JobsAI 19:55 - 20:30: Networking

– Introduction Fabian Schmidt, PhD Student, KTH

Fabian is working on the ALEC2 project under the supervision of Professor Vladimir Vlassov and Associate Professor Amir Hossein Payberah at KTH Royal Institute of Technology.

Presentations:

E-FlowCast – Forecasting Cross-Border Energy with Serverless ML Rosamelia Carioni - KTH Student Eric Banzuzi - KTH Student

How do you build a serverless ML system that predicts real-time electricity flows? The energy grid is one of the world's most complex and volatile systems. Prices fluctuate, demand spikes and renewable sources make forecasting difficult. To stay ahead, traders, operators, and policymakers need reliable predictions. E-FlowCast is a serverless ML system designed to address one area of this challenge, providing real-time electricity flow predictions for the next 24 hours.

Speakers Bio: Rosamelia is a final-year master’s student in Machine Learning at KTH. She has a BSc in Data Science and AI from Maastricht University. Through research and internships, she has worked on predicting donor churn, building an NLP-to-SQL chatbot to improve data accessibility, developing an energy-weather visualization tool for real-time trading insights, and enhancing gunshot detection for wildlife conservation.

Eric is a final-year master's student in Machine Learning at KTH, with interests and skills in ML, data engineering, and software development. Prior to KTH, he completed a BSc in Data Science and AI at Maastricht University in 2023.

Real-time weather-based transit delay forecasting Paul Hübner - KTH Student Jonas Müller - KTH Student

When snow falls, there are often drastic consequences for the public. Public transportation of all types experiences sudden large delays, leading to people being stuck waiting at stops and missing transfers. By taking local weather forecasts into account, such travel delays could be predicted in real-time. Based on historical and live transit delay data from Gävleborg County as well as Open-Meteo forecasts, we present a real-time serverless delay forecasting dashboard powered by machine learning.

Speakers Bio: Paul studied Computer Science & Engineering at TU Delft, specializing in the Machine Learning and Data Science track. He is pursuing further studies in Software Engineering of Distributed Systems at KTH.

Jonas is pursuing a Master’s in Software Engineering of Distributed Systems at KTH, where he is currently researching conflict-free replicated data types in the context of edge computing for his thesis.

The Ultimate 1Million Movies Dataset Martín Bravo - KTH Student

This serverless ML system predicts IMDb ratings using a dynamic Kaggle dataset. It features four automated pipelines: historical data backfilling, daily feature updates, model training, and inference for new movies. A user-friendly interface allows users to explore movies, view predicted ratings, and compare them with actual IMDb scores.

Speaker Bio: Martín is a Computer Science and Engineering student from Chile, currently an exchange student at KTH Royal Institute of Technology in Stockholm. He has worked with the National Center for Artificial Intelligence and SoyMomo in Chile and is currently interning at Hopsworks as a Machine Learning Engineer, focusing on LLMs and ML pipelines.

JobsAI Kolumbus Lindh - KTH Student

Finding the right job among thousands of listings can be overwhelming. JobsAI streamlines this process using vector embeddings and similarity search to match users’ resumes with the most relevant job postings. By leveraging Natural Language Processing (NLP) and machine learning, the platform eliminates inefficiencies associated with traditional job search methods. JobsAI retrieves job listings via Arbetsförmedlingen’s JobStream API and processes user-uploaded resumes to calculate compatibility scores.

Speaker Bio: Kolumbus is a master's student in Industrial Engineering and Management at KTH, specializing in Machine Learning. With a background in AI consulting and software development, he enjoys finding practical ways to integrate AI into businesses. –

About the event

Date: February 27th, 17:30 - 20:30 Location: Hopsworks Office (Åsögatan 119, Plan 2, 116 24 Stockholm) The venue hosting us is the Hopsworks Office. As the office is sometimes difficult to locate we have made this map for everyone to follow. Directions: 2-minute walk from Medborgarplatsen. Tickets: Sign up required. Anyone who is not on the list will not get in. The event is free of charge. Capacity: Space is limited to 60 participants. If you are signed up but unable to attend, please change your RSVP by February 26th. Food and drinks: Food and drinks will be provided. Questions: Please contact the meetup organizers.

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Code of Conduct The NumFOCUS Code of Conduct applies to this event; please familiarize yourself with it before attending. If you have any questions or concerns regarding the Code of Conduct, please contact the organizers.

Details

DON'T MISS DSC'S COLLIDE DATA CONFERENCE ON OCTOBER 3-4 IN ATLANTA! REGISTER HERE WITH DSATL'S VIP PROMO CODE Get ready to witness the collision of data and industry at Data Science Connect's COLLIDE Data Science Conference IN-PERSON on October 3-4, 2023 in Atlanta, Georgia. This event will showcase the latest trends and advancements in data-driven decision making and how it is revolutionizing every industry. As the field of data science continues to rapidly evolve, COLLIDE will offer insights into how data is transforming the way businesses operate and make decisions. Attendees will hear from leading experts in the field and have the opportunity to engage in lively discussions and networking opportunities. Join us at COLLIDE and discover how the collision of data and industry is shaping our present and revolutionizing our future. Get ready to COLLIDE with the future of data-driven industry!

AGENDA CONFERENCE PRESENTATIONS, INDUSTRY PANELS, AND HANDS-ON WORKSHOPS DAY 1 - Wednesday, October 3 from 9AM - 5PM EST DAY 2 - Thursday, October 4 from 9AM - 5PM EST 2023 SPEAKERS TO BE ANNOUNCED PAST DSC SPEAKERS INCLUDE: Melvin Greer\, PhD \| Chief Data Scientist @ Intel 🖥️ Juan Gorricho \| Former Chief Data Officer @ Visa 💳 Lo Li \| CTO @ Spanx 👠 Inderpal Bhandari\, PhD \| Global Chief Data Officer @ IBM 👩🏽‍💻 Charles Duze \| Analytics Leadership @ Meta 🌐 Eric Schmidt \| Global Director - Data & Advanced Analytics @ The Coca-Cola Company 🥤 Sol Rashidi \| Chief Analytics Officer @ Estee Lauder 💄 Ben Dundee \| Lead Director Data Science and Experimentation @ CVS Health ⚕️ Hua Ai \| General Manager Predictive Modeling @ Delta ✈️ Bharath Varma Sagi \| Senior Data Scientist @ Starbucks 🍵 Anshul Agarwal \| Director of Decision Science @ The Walt Disney Company 🎥 Francisco Rius \| Head of Data Science @ Minecraft ⛏️ Doug Wynne \| Director of Strategic Analytics @ Comcast 📡 Faizan Javed \| Senior Director of Data Science & Engineering @ Kaiser Permanente 🏥 Leondra Gonzalez \| Senior Data & Applied Scientist @ Microsoft 🧑‍💻 Meet Patel \| Senior Director\, Global Advanced Analytics @ Kellogg Company 🥣 Nechama Katan \| Director of Data Science @ Pfizer 💊 Bill Franks \| Director\, Center for Data Science and Analytics @ KSU🎓 Joel Amick CISSP\, MBA\, MSIT \| Director\, Cyber Automation\, Analytics & Data Science @ TIAA 📈 Selma Dogic \| Sr. Manager\, Analytics COE @ Carter's 👶

Register on the event website to receive joining link: https://www.aicamp.ai/event/eventdetails/W2023071109

Description: Join us for a half-day event featuring top AI/Ml influencers and leaders in the industry. The central focus will be generative AI. We will feature discussions on building your own custom LLMs, building simple AI agents, and the future of generative AI.

Previously we have had Silicon Valley legends such as Eric Schmidt, Peter Norvig, Pieter Abbeel, & Alon Halevy deliver riveting fireside chats about AI, deep learning, and more. We will slowly reveal more about our exciting guests joining us in the coming weeks.

Visit the event website for updated speakers, agenda and RSVP: https://www.aicamp.ai/event/eventdetails/W2023071109

Register on the event website to receive joining link: https://www.aicamp.ai/event/eventdetails/W2023071109

Description: Join us for a half-day event featuring top AI/Ml influencers and leaders in the industry. The central focus will be generative AI. We will feature discussions on building your own custom LLMs, building simple AI agents, and the future of generative AI.

Previously we have had Silicon Valley legends such as Eric Schmidt, Peter Norvig, Pieter Abbeel, & Alon Halevy deliver riveting fireside chats about AI, deep learning, and more. We will slowly reveal more about our exciting guests joining us in the coming weeks.

Visit the event website for updated speakers, agenda and RSVP: https://www.aicamp.ai/event/eventdetails/W2023071109

0:00 Open 6:08 Ali Ghodsi & Marc Andreessen 32:06 Reynold Xin 48:09 Michael Armbrust 1:00:00 Matei Zaharia & Panel 1:27:10 Hannes Muhleisen 01:37:43 Harrison Chase 01:49:15 Lin Qiao 02:05:03 Jitendra Malik 02:21:15 Arsalan & Eric Schmidt

This episode features a discussion with statistics PhD student Zach Seeskin about a project he was involved in as part of the Eric and Wendy Schmidt Data Science for Social Good Summer Fellowship.  The project involved exploring the relationship (if any) between streetlight outages and crime in the City of Chicago.  We discuss how the data was accessed via the City of Chicago data portal, how the analysis was done, and what correlations were discovered in the data.  Won't you listen and hear what was found?