Our meetups will focus on practical tips and tricks in doing tasks with these programming languages. We will also plan workshops, tutorials, etc. We will identify which language will be covered in each event.
This group, alongside the other Data Community DC (http://www.datacommunitydc.org) groups, is dedicated to bringing together the DC metropolitan area statistical programming practitioners, hackers, students and academics to exchange knowledge, inspire new users, and spur the adoption of many of these tools in innovative research and commercial applications.
GWU Norma Lee and Morton Funger Hall, Room[masked] G St. NW, Washington, DC
6:30pm – 7:00pm Networking and Refreshments
7:00pm – 7:10pm Introduction, Announcements
7:10pm – 7:40pm Presentation
7:40pm – 7:55pm Q&A
8:00pm – 8:30pm Data Drinks at Tonic (2036 G St NW)
This Meetup is co-hosted by
- Data Science DC (https://www.meetup.com/Data-Science-DC/) and
- Statistical Programming DC (https://www.meetup.com/stats-prog-dc/)!
Developed by Google and written in Python, TensorFlow is the most popular deep learning framework. However, it is not perfect. To improve the developer experience, consolidate functionality, and expand on the ability to be deployed, TensorFlow 2 was developed. As of September 30th 2019, TensorFlow 2 is out of alpha and has been given a full release. This talk will address the motivations behind TensorFlow 2 and how it fixes some of the pain points of its predecessor. I will also include a practical example of how to effectively develop deep learning models using some of TensorFlow 2's features.
ABOUT THE SPEAKER
Elliott is a Data Scientist at BlackSky inc., a Virginia Based Geospatial company. For the past 5 years he has worked on developing and productizing several aspects of machine learning, particularly in the areas of computer vision and natural language processing. He is always interested in what is making an impact in the world of understanding data.
Outside of work he attends several local DC meetups and loves to engage with and learn from others in the field.