Important: You need to arrive between 4:00 and 4:30 pm and verify your vaccine status. Enter through the 9th avenue entrance (75 9th avenue) located on 9th ave and 16th street

Guests who are not able to provide visual proof of vaccination will not be permitted to enter Google NYC buildings.

Valid Forms of Vaccination Verification:

• Physical vaccination card
• Photo of vaccination card
• Official Digital records of vaccination from your vaccine provider and/or public health authority 

Please be considerate and RSVP only if you plan to show up.

The event is first come for 100 attendees and after that "doors close".

You are encouraged to show up on time to ensure your spot!

https://bit.ly/AI-ML-Google-NYC

Agenda:

4:00 pm - Doors Open and Check In

4:30 pm - 5:30 pm: Food and Networking

5:30 pm - 5:40 pm: Welcome/Sponsor intro

5:40 pm - 7:40 pm: Tech Talks

7:40 pm - 8:00 pm: Lucky Draw & Mingle

Tech Talk 1: Getting started with KerasNLP

Speaker: Shilpa Kancharla, Developer Relations Engineer at Google

Abstract: KerasNLP is a natural language processing library that allows you to use easily customizable components to produce state-of-the-art NLP models.

In this workshop, you will begin with using pre-trained Transformers (including BERT) to classify text, then you will learn to fine-tune them on your own data, and finally work up to building your own Transformers from scratch.

Regardless of where you are in your NLP journey, we will cover concepts that relate to your skill level and pave the way for future learning paths. This workshop starts with content for total beginners, then works up to intermediate and advanced developers, so you will be sure to learn something along the way. All skill levels are welcome!

Tech Talk 2: ML Product Development Process In Practices

Speaker: Funmi Doro, formerly ML Platform Lead @ Spotify (on sabbatical now)

Abstract: Many product teams are accustomed to the lean, agile, iterative approach to product development, where continuous value is delivered to users using a Build, Measure, Learn Loop.

While this iterative approach is well-suited to many applied ML problems, it can take some effort for ML product teams to adapt this to their ways of working.

During this talk, we will explore tips for validating assumptions, minimizing risks, and delivering value to users quickly and collaboratively.

Important: Upon arrival to Google NYC, you will need to verify your vaccine status at a staffed entry point/registration desk and provide visual proof of your vaccination status to registration staff/security in order to attend.