Next Meetup

Scaling Deep Learning @ Twitter
Come join us as we dive into how we’re applying deep learning across Twitter and solving some of the challenges our engineers face. In order to attend you must RSVP on the registration link below. (registration on is not an option and will be closed) AGENDA: 6pm Doors Open 6:30pm Tech Talks Begin 7:15pm Q&A 7:30 - 8pm Networking TOPICS INCLUDE: CHALLENGES IN RECOMMENDER SYSTEMS - ASHISH BANSAL “Twitter has amazing and unique content that is generated at an enormous velocity internationally. A constant challenge is how to find the relevant content for users so that they can engage in the conversation. Approaches span collaborative filtering and content based recommendation systems for different use cases. This talk gives insight into unique recommendation system challenges at Twitter’s scale and what makes this a fun and challenging task.” TWITTER'S ML PLATFORM: DEEPBIRD WITH CIBELE HALASZ “Twitter is a company with massive amounts of data. Thus, it is no wonder that the company applies machine learning in various ways: from Timeline Ranking to Ads. This talk will be focused on our most recent ML platform, which is built on top of (Python) Tensorflow. Particularly, how it allows for teams inside the company to run their models in production at Twitter’s scale.” EMBEDDINGS @ TWITTER WITH ABHISHEK TAYAL “This talk dives into how Cortex is making entity embeddings a first-class citizen within Twitter’s ML platform by commoditizing tools and pipelines that create high-quality, regularly retrained, benchmarked, and centrally hosted embeddings.” PRODUCTIONIZING ML WITH WORKFLOWS @ TWITTER WITH NEWTON LE & XIAO ZHU “In an effort to reduce the cost of maintenance of production machine learning pipelines, improve engineering productivity, and increase the rate of experimentation, Cortex developed ML Workflows, a tool based on Airflow, designed to automate, schedule, and share machine learning pipelines at Twitter. We will discuss ML Workflows and how it interfaces with Twitter’s other ML platform tools, such as hyperparameter tuning, ML repository, and ML dashboard”

Twitter HQ

1355 Market St. · San Francisco, CA

What we're about

Twitter is for known what’s happening in the world and what people are talking about in real-time. Realizing this requires building state of the art real-time systems and using cutting edge technologies in the areas of machine learning, infrastructure, big data & more.

Join us as we learn about the people and work behind Twitter Engineering.

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