Sorry folks. We'll re-schedule soon!

PDX Speech and Language Processing Happy Hour is an informal gathering of individuals working in computational linguistics, speech, and natural language processing in the Portland metro area. No talks, just socializing, but shop talk encouraged. Some folks will be around 7-10, so drop in as your schedule permits. At Orenco Taphouse.

Rescheduled! PDX Speech and Language Processing Happy Hour is an informal gathering of individuals working in computational linguistics, speech, and natural language processing in the Portland metro area. No talks, just socializing, but shop talk encouraged. Some folks will be around 7-10, so drop in as your schedule permits. At Orenco Taphouse.

PDX Speech and Language Processing Happy Hour is an informal gathering of individuals working in computational linguistics, speech, and natural language processing in the Portland metro area. No talks, just socializing, but shop talk encouraged. Some folks will be around 7-10, so drop in as your schedule permits. At the Lucky Labrador Beer Hall.

PDX Speech and Language Processing Happy Hour is an informal gathering of individuals working in computational linguistics, speech, and natural language processing in the Portland metro area. No talks, just socializing, but shop talk encouraged. Some folks will be around 7-10, so drop in as your schedule permits. See you at EastBurn!

We'll have a short presentation on deep NLP and review the paper "StarSpace: Embed All The Things!"

The major vendors in cloud-based services are starting to provide machine learning as a service, such as Google Cloud AutoML Natural Language and Azure Language Understanding (LUIS). Jim Tyhurst will give a brief demonstration of IBM Watson Natural Language Classifier service (https://www.ibm.com/watson/services/natural-language-classifier/), which enables you to build a custom classifier with no programming. Just create a new instance and submit training data. When the system has finished training, you can submit a document through a web API. The system responds with JSON, giving a list of some possible categories with a confidence score associated with each category. We will discuss some of the advantages and disadvantages of this service.

StarSpace: Embed All The Things! - describes a general-purpose neural embedding model that can solve a wide variety of problems: labeling tasks such as text classification, ranking tasks such as information retrieval/web search, collaborative filtering-based or content-based recommendation, embedding of multi-relational graphs, and learning word, sentence or document level embeddings. https://arxiv.org/abs/1709.03856

Details
Same place, still looking for speakers. If you have anything you would like to present, let me know!

If you need parking, there's a parking deck below Safeway.

Agenda:

6:00 p.m.: Food, beverage, and networking

6:40 p.m.: Welcome message by Karl Fezer

6:45 p.m: Speaker 1: "Transfer Learning, or How to Stand on the Shoulders of Giants" - James DiPadua
7:30 p.m: Speaker 2: "Quantum Mechanics for Modeling Composite Semantic Spaces" - Connor Favreau
8:15 p.m.- 8:30: Project Ideas. Pitch your Project Ideas to this meetup group

8:30: End

Speaker 1 Details:

Abstract:

There's been a mountain of research into Deep Neural Networks' practical applications in image, audio and text processing. But these deep networks are often built on large corpuses of data (such as ImageNet or Wikipedia).

But that may not apply directly to your domain. Gathering data specific to your problem space may not only be a lengthy process but an expensive one too. That makes the business win a hard sell.

Transfer Learning can dramatically eliminate many of those problems, quickly.

In 'How to stand on the shoulders of giants,' we'll discuss the research background into Transfer Learning and how to implement the process in either Keras or PyTorch. The goal is for listeners to feel comfortable with the concept and prepared to begin researching an application in their workspaces.

Bio:

James is a wanderer, tinkerer, and ponderer. Not one to be pinned down, he's more comfortable in the abstract than in the known. He embraces ambiguity with a bearhug. That's a trick of course. He bear hugs the ambiguity into little mathematical boxes and then says "Dance!" and, oh, how that ambiguity dances! James currently hangs his hat at Vacasa where he works as a Senior Data Scientist tackling a myriad of growth-objectives with engineering and machine learning.

Speaker 2 Details:

Five years ago, Word2Vec offered a leap forward for the average data scientist to perform efficient algorithms in Natural Language Processing. From a body of text, Word2Vec generates a semantic space, in which the trained word vectors are often highly associated with their meaning. The next leap, a semantic space for phrases and sentences, proves tougher both computationally and in faithfully representing a composite meaning over multiple words. Surprisingly, quantifying particle interactions a la quantum mechanics shares close mathematical similarity to quantifying the meaning of words, phrases, and sentences. In this talk, I will provide an overview of current techniques in modeling language past word vectors, as well as point out the quantum mechanical aspects of these techniques. Emphasis will be placed on the “Compositional Distributional Semantics” model for the task of identifying word ambiguity."

Join us for a demo of analyzing and plotting Twitter sentiment using Python and Natural Language Processing. I'll demo how to use techniques such as tokenizing, lemmatizing, corpora, wordnet, and building a machine learning classifiers such as Logistic Regression, SVC, and SGDC.

I wonder what the Twitter sentiment will be on our president on demo day?

If you would like to join the discussion check us out on Zoom https://zoom.us/j/7891236789.

Do you want to learn and share your passion in a supportive community? Knowledge Mavens is an ethos of sharing, creativity, and inspiration.

Our Meetup provides an opportunity to "Show and Tell" followed by feedback and Q&A. You'll have the opportunity to share with our channels such as Meetup, GitHub, YouTube, and Facebook to connect with more passionate people.

The second half of our session we'll collaborate on new topics. The winner wins an award for the most interesting topic and the opportunity to share in an upcoming session.

Come join us for the kick-off of Dynamic Talks in Portland!

Dynamic Talks is an ongoing meetup series featuring technical talks from some of the leading experts in tech in major cities around the US. Enjoy talks about the most innovative subjects in: AI, ML, voice platforms, the Cloud and search. Every event is free, with complimentary food and drinks.

In Portland, the topic of our first event will be “Voice Platforms, Conversational Commerce and NLU”. The speakers for this event will be Victoria Livschitz, Founder and CTO of Grid Dynamics, and Eugene Steinberg, Technical Fellow at Grid Dynamics. Come enjoy a night of technical talks and networking opportunities at CoLab Coworking Portland in Tigard. We hope to see you there!

Agenda

[6:00PM - 6:30PM]: Guests arrive, pizza and drinks are served

[6:30PM - 7:15PM]: First talk will be presented by Victoria Livschitz on “Conversational commerce: emerging architectures for smart & useful chatbots", followed by a Q&A

[7:15PM - 7:30PM]: Networking break

[7:30PM - 8:15PM]: Second talk will be presented by Eugene Steinberg on "Not your fathers search engine: deep learning applications for e-commerce search", followed by a Q&A

[8:15PM] - 9:00PM]: More networking and the event ends

Talk details:

Victoria Livschitz's talk details:

Title: "Conversational commerce: emerging architectures for smart & useful chatbots"

Abstract: Smart speakers and messaging apps are increasing in popularity due to their convenience, intuitive usage, and new user experiences. Companies are racing to develop voice interfaces and AI technologies in order to utilize smart speakers and messaging platforms as a sales channel.

We are introducing Grid Genie, a completely open source, multi-device, conversational commerce platform. With this technology, we can help you engineer a powerful platform to combine your Alexa skills, Google actions, and Facebook Messenger into a single seamless experience.

Eugene Steinberg's talk details:

Title: "Not your fathers search engine: deep learning applications for e-commerce search"

Abstract: In this talk, we will discuss how recent advancements in artificial intelligence are transforming traditional search technologies. Deep learning-based image analysis and natural language processing open exciting new horizons for search and recommendation applications across the industries. We’ll talk about how deep learning models can help conventional search engines to achieve better relevance. We will share our experience implementing innovative solutions for online retailers, finance and high tech customers.

Un-Redacting the Mueller Report and Abstracting the News with NLP By Hobson Lane and Al Kari

Hobson will show you how to write a python "mad-libber" that can unredact the Mueller Report. The first person to correctly predict the next word better than the mad-libber will win an autographed copy of Natural Language Processing in Action, a book produced through open collaboration among Portland Python User Group Members, led by Cole Howard and Hannes Hapke. Then Hobson and Al Kari will show you how they use this same state-of-the-art language model to generate meaningful abstractive summaries of technical documents like clinical medical records.

About our speakers: Hobson Lane's first Python apps were built with the help of friends at the Portland Python User Group almost a decade ago. Since then he's been using Python for everything from chatbots to building energy consumption forecasting. He's now CTO at Deep Canopy where they build smart cameras for industry. In his spare time Hobson teaches Python and data science on Springboard.com, Thinkful.com, and Totalgood.com and preaches crackpot ideas for harnessing the pending AI explosion for the greater good.

Al Kari is a Google Developer Expert (GDE) in Machine Learning, organizer of the TensorFlow-Northwest meetup group and CEO of Manceps, an engineering company focused on providing intelligent automation solutions to innovative businesses.

Join us afterward at Bailey's Upper Lip Upstairs Taproom 213 SW Broadway to continue the discussion over a beverage.

Do you have something you'd like to share?

PDX Python on Twitter (http://twitter.com/pdxpython)

Portland Python Web Site (http://pdxpython.io/)