Please Note: This is an ONLINE event. The online streaming link will be sent after registration.

Google Developers Space, Singapore is a home for developers and startups from around the region to learn, connect, engage, and be inspired.

Join *La Kopi @ Developer Space and hear developers from our community share about their best practices on Data Science methodologies, processes and tools.

Are you working on Data Science projects that you would be happy to share with the community? Simply fill up our form here and we will be in touch soon.

* Singlish: Literally means ‘stir-coffee’, also means 'to get together'.



Time Agenda
8:00pm Introduction
Developer Open Mic Session

  • Automate Boring Stuff Data Science Way
    Florentin Anggraini Purnama, Data Analyst, Traveloka

    Have you ever used Slack as a work diary? Do you have lots of private channels where you store your codes and important scripts? Do you have anxiety that one day all your hard-built knowledge base will be lost when you lose access to the workspace?

    This session will show you how to solve them. After this talk, you'll know how to create automatic cronjob for backing up any Slack channel you want to BigQuery.

  • Hey, Customer Support: Using Topic Modeling to Dig into Tweeted Requests

    Alexandra Khoo, Cultural Data Scientist, Synthesis

    Are you looking for a good way to extract "hidden" patterns from large volumes of short text? Through the lens of uncovering sources of discontent in tweets sent to an ecommerce platform for customer support, we will walk through text processing methods and discuss how best to use topic models.

    While the focus is on the use of the Non-Negative Matrix Factorisation model, this talk will briefly touch on two other common methods: Latent Dirichlet Allocation and Biterm topic want to BigQuery.

  • Simkit - Generative & Probabilistic Modelling Framework for Reinforcement Learning

    Jet New, Machine Learning Engineer Intern, Grab

    Many pricing and decision making problems at the core of Grab's ride-hailing and deliveries business can be formulated as reinforcement learning problems, with interactions of millions of passengers, drivers and merchants from over 65 cities across the Southeast Asia region.

    In Jet's internship as a Machine Learning Engineer, he worked with scientists and engineers to develop Simkit, a new framework for building generative and probabilistic models, in order to train reinforcement learning agents to be served in production services and make optimal, real-time decisions.

Sign up as a speaker for our future La Kopi sessions here.

8:45pm End


See you at La Kopi!