Cibele is a Software Engineer at Twitter Cortex, where she helps to build Twitter’s deep learning platform. Prior to working at Twitter, Cibele worked at Apple as a Data Scientist and Systems Design Engineer; and at Analog Devices as Product Applications Engineer . At Analog Devices, she worked on building machine learning algorithms that use smartphone sensors to understand a person’s behavior. Cibele obtained her B.S. from Stanford University in Electrical Engineering and Physics and her M.S. from the California Institute of Technology in Electrical Engineering with an emphasis in Computer Vision and Machine Learning.
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. We will give you an idea of how we are doing ML at Twitter’s scale and what our platform provides on top of Tensorflow.
Machine Learning has allowed Twitter to drive engagement, promote healthier conversations, and deliver catered advertisements. Over the past year, we have been working on a new chapter of ML at Twitter by migrating our machine learning platform from Lua Torch to (Python) Tensorflow. This talk will be mainly focusing on the Machine Learning framework we have been developing on top of Tensorflow. More especially, how it allows for teams inside the company to run their models in production at Twitter’s scale.
We plan to discuss:
- Our migration from Lua Torch to Tensorflow
- The additions of our framework on top of Tensorflow
- How we productionalize our model