# TensorFlow 2.0
TensorFlow has emerged as one of the most popular Deep Learning frameworks in-use today. It has by far more users and contributors than any other project, and is continuing its upward trajectory with the release of the TensorFlow 2.0 API.
This is a technical talk, very much geared towards engineers; especially those who need to scale high-demand workloads using a platform which supports big data processing and has a great compliance story.
There are many new features of TensorFlow 2.0. Jerome will discuss eager execution, notebook accessible TensorBoards, tighter integration with Keras and more.
Jerome will also demonstrate how edge calculations can be accelerated with tensorflow.js, which runs completely in the browser and provides much faster model serving.
TensorFlow is well on the way to becoming the standard for all things deep learning... come join us to find out more!
The venue and catering will be provided by our Key Sponsor: IBM. Thank you!
The event may be filmed and the recording may be made publicly available. Our meetups are inclusive and harassment is not tolerated. For more information, see our Code of Conduct: https://www.meetup.com/Auckland-AI-Meetup/messages/boards/thread/50720238
You can drop into this event at any time.
Jerome is a developer advocate, data scientist, and member of the IBM Center for Open source Data and AI Technologies (CODAIT). He works at CODAIT with open source frameworks for Big Data, Machine Learning and Deep Learning.
He has a BS in Chemical Engineering from UC Berkeley, a PhD in Computational Biophysics from UC San Francisco, and has carried out postdoctoral research in biophysics and bioinformatics at UC Berkeley; Lawrence Berkeley and Livermore Laboratories; and at Stanford as an OpenMM Fellow.
Just prior to joining IBM in 2015, Jerome completed the Insight Data Engineering program.