A Deep Dive into Natural Language Processing in Production
A Deep Dive into Natural Language Processing in Production
We are excited to be back with not one, but TWO in-person workshops!
Join us on March 6th & 8th from 6h00 PM to 9h00 PM and get to learn about our Beirut AI & AWS community and indulge in the world of Natural Language Processing.
⚠️ If you wish to attend both dates make sure you register for both dates ⚠️
March 6: Sentiment Analysis using Hugging Face Transformer
Dive into the field of Natural Language Processing and get introduced to the State of the Art Transformers models in production. We will discuss the common use cases, practices, and state-of-the-art models nowadays then you will get your hands dirty and train your own transformers for Sentiment Analysis.
March 8: Natural Language Processing in Production using AWS tools
Learn about the AWS ecosystem and how you can as an AI specialist benefits from these tools. You will learn how to deploy your trained transformer model in an AWS environment and monitor its performance in production.
No machine learning background is required, anyone familiar with coding (preferably in Python) can attend.
Make sure you bring with you a laptop so you can code along! 💻
P.S: Seats are limited so please only register for the workshop that you know you can attend!
🍕 Pizza & Drinks will be available after the workshop
A big thank you to our sponsors Berytech, Zaka, and Unicloud for supporting this workshop.
Instructors
Jana Kabrit, a passionate AI enthusiast, has been a volunteer at Beirut AI since 2019. She has given 20+ workshops on AI. She is currently an AI Developer at Assentify and Office Hours Instructor at Zaka.
Hadi Abou Daya, is a passionate AI enthusiast, mostly self-taught, with a strong background in machine learning and deep learning. He is a Machine Learning specialist at Mobile Arts and a previous computer vision developer at Decentra Tech. He trained and deployed models to both edge devices and the cloud using technologies like TensorFlow, PyTorch, Nvidia TAO Toolkit, and AWS.