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Thursday
Sep 19, 2019
@DAMAPDX Sept. Chapter Meeting, Recent Advances in Natural Language Processing – (Some) Theory & Applications
Standard Insurance Tower Atrium (900 SW 5th)

Presented by Joachim Rahmfeld, Ph.D Lecturer at UC Berkeley

Today’s vast volumes of language-based, unstructured, electronic data found in various form factors such as blogs, email, social media, or web sites, promises competitive advantages for those who can extract business-relevant information most effectively and efficiently. Natural Language Processing (NLP) holds the key in leveraging this type of data in order to answer and respond to important questions such as, “What is the perception of my company in the Twittersphere?”, “Are these reviews largely positive or negative?”, “What is the translation of this in Spanish?”, “This document has the answer to my question somewhere… but where?”, “Are these products similar?”

Particularly over the last five years, revolutionary advances in NLP-related Deep Learning algorithms combined with dramatically increased compute resources have created unprecedented opportunities to not only answer natural language questions with greater accuracy and speed, but often also while requiring significantly less training data.

In this session, we will provide an overview of these advances and how you can make use of them. A particular focus will be transfer learning where large, pretrained models, such as Google’s BERT model, can be leveraged for a broad set of NLP use cases delivering excellent results, and enabling you to answer questions that were not possible to answer just a few years ago.

So this is a great time to learn about recent NLP developments and go through explicit examples.

About the Speaker

Joachim started his career in theoretical physics before leaving academia and joining the IT industry. For over a decade, he held various leadership positions in professional services, business development and sales at Sun Microsystems, VMware, and Hitachi Data Systems. In 2015, Joachim returned to his quantitative roots and obtained a Master of Information and Data Science from UC Berkeley. Most recently, Joachim managed a Data Science research team at Edison Software. He currently lectures at UC Berkeley on Natural Language Processing with Deep learning and is working on various NLP projects.

When

Sept 19th, 2019 (Chapter meetings held on third Thursday of the month)

Schedule

8:30 – 9:00 am – Sign In 9:00 – 10:15 am – Presentation 10:15 – 10:30 am – Break, Chapter Announcements 10:30 – 11:30 am – Presentation continued

Standard Insurance Tower Atrium (900 SW 5th, please note Standard Ins. has multiple downtown locations)

Cost

Free for members (including ALL employees of corporate members) $15 for non-members $5 for students with valid student ID

Standard Insurance Center, 900 SW 5th Ave, Portland, OR 97204, USA

Website
Thursday
Oct 22, 2020
DAMA Day 2020: "Data... In SPACE!" with NASA Scientists, sponsored by Snowflake
Virtual

Presented by NASA Scientists Sponsored by Snowflake

Calling all data enthusiasts and/or space nerds in Portland, Oregon and beyond. Join us for an exciting, all-day virtual event with NASA scientists. Attendees will work with actual NASA data and have an opportunity to collaborate on matters of data analysis directly with our presenters.

Opening Remarks: 8:30 AM: DAMA PDX Board

Morning Session: 9AM – 11:30 AM: Eric Lyness and Victoria Da-Poian, NASA

Eric Lyness is the NASA software and operations lead at Goddard Space Flight Center for the Mars Organic Molecule Analyzer on the ExoMars 2020 rover and Victoria Da-Poian is an Aerospace Engineer. They will present their talk, Machine Learning to Find Life on Mars and Beyond.

In 2021 the European ExoMars rover will land on Mars with the Mars Organic Molecular Analyzer (MOMA) laboratory to analyze soil samples searching for past or present life. NASA is developing machine learning algorithms to help the scientists more quickly analyze the data when it arrives from Mars. In this talk, we will present the current work using MOMA mass spectrometer data acquired during ground testing. Using this data we are aiding the scientists by matching new spectra with the most similar spectra from past experiments. We will present the nuances of mass spectra, our limitations with respect to data, and our approach to the problem. We hope to elicit feedback from the attendees.

More details at https://phys.org/news/2020-06-nasa-life-mars.html.

30 minute Break

Lunch Session: 12:00 – 1:00 PM: Snowflake Presentation, Drew Swanson and Brian Whittington

30 minute Break

Afternoon Session: 1:30 PM – 3:30PM: Details soon!

15 minute Break

Closing Remarks and Next Steps: 3:45 – 4:00 PM: DAMA PDX Board

Times above may be revised in the days before our event.

Event will be presented via a Zoom bridge. Analytical discussions and collaboration will be hosted via a Slack workspace that will begin on event day and last for a few weeks afterwards. This is a BYOAE (bring your own analytical environment). However, attendees will have access to the data via Snowflake and to notebook templates via Zepl.

Pre-event tasks for analysis setup will be shared on 10/19 via email.

Date – Thursday, Oct. 22nd Time – 8:30 – 4:00pm

NOTE: This is an all day event

Website
Friday
Apr 23
A Day in the Life of a Data Scientist and How to Get There - Tech Talk with Kent Gray
The Tech Academy

Tech Academy graduate Kent Gray joins us to share his journey from boot camp student to data scientist in this week's Tech Talk.

Kent works as a service Data Scientist at Kubota Tractor Corporation, and has several years experience as an analyst since graduating from The Tech Academy in 2016. Come learn what a day in the life of a data scientist is like and get advice on how to break into the industry!

Meet with us virtually on April 23rd at 1pm Pacific time for some networking and fun!

Register on MeetUp to attend: https://www.meetup.com/techacademy/events/277240087/

Website