Demo Day! for Employers and Job Seekers
Details
EMPLOYERS: Looking for Tech Talent for your company? Join us for networking with the presenters via Zoom breakout rooms during the second part of the event!
Get your invitation by registering here:
https://docs.google.com/forms/d/e/1FAIpQLSeH2np1O-yorU1lWGHdixUu8jJ-zRszmr7puwrptaCOGMVQng/viewform
We are looking to bring together job seekers and hiring partners into the "same room" in a one-of-a-kind networking event.
5 PM - 6 PM EST:
Demo/Presentations
(live-streamed on YouTube)
6 PM - 7 PM EST:
Network/Q&A
(by invitation)
CONFIRMED SPEAKERS/ AGENDA DETAILS:
š¤ Greg Feliu
š» Data Analyst/Data Scientist
š NYC / Remote
This talk is an exploration into Mexican immigration in the United
States using restaurant names. I found that people from all over Mexico
immigrated to the U.S. in about equal numbers in the U.S. cities
examined but there were some clear cases of chain migration from one
Mexican region to one U.S. city.
~
š¤ Kei Nemoto
š» Software Engineer/Data Analyst/Machine Learning
š NYC / SF / LA / Remote
In this demo, I will present ReproNETs, a Machine Learning as a Service for named entity transliteration models. Users can get real-time predictions by state-of-the-art models via HTTP requests or a web GUI. It uses a microservice architecture to achieve scalability and maintainability. To the best of my knowledge, there is no service to provide transliteration as a service.
~
š¤ Sasha Prokhorova
š» Data Analyst/Data Scientist
š SF
Presentation abstract:
My project involves gathering The New York Times historical data through the Archive API, running sentiment analysis using NLTK Vader, producing visualizations using Seaborn and Tableau, and topic modeling by means of SpaCy and gensim libraries. The goal of this data journalism research was to investigate gender representation in print in order to promote equality and opportunity.
~
š¤ Mason Ellard
š» Data Analyst/Data Scientist
š NYC / SF / LA / Chicago / Remote
In this project, I built a gentrification classifier using American Community Survey data and scaled the model to the entire US using PySpark and AWS. I found education and popular methods of transportation in surrounding neighborhoods to be significant indicators of gentrification - supporting the theory that gentrification is being fueled by an inflow of educated professionals targeting highly amenable neighborhoods.
~
š¤ Julia Nguyen
š» Data Analyst/Data Scientist
š SF / LA / Remote
In this demo, I will present a project where I developed a convolutional neural network that can detect areas of urban development in satellite images. I applied this model to satellite images of various cities to measure urban sprawl.
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š¤ Julia Qiao
š» Data Analyst/Data Scientist
š NYC / SF / Remote
Who is the millennial homeowner? Interpreting demographic characteristics via classification.
~
š¤ Harry John Shephard
š» Data Analyst/Data Scientist
š Worldwide
I took a look at communities where people connect over disordered eating and parse through their language to better understand what distinguishes one community from another and to seek out patterns in the conversations people have when they feel they have permission to share a part of their lives they usually keep sealed off from the world
~
š¤ Yaakov Bressler
š» Software Engineer/Data Scientist
š NYC
ORMs (Object Relational Mappers) are pretty nifty things ā they allow you to interact with SQL databases as python objects. In this hands-on overview, I'll demonstrate how SQLAlchemy can be used to create a database to represent Broadway shows ā using 100% python!
~
š¤ Neda Saleem
š» Data Analyst/Data Scientist
š LA / SoCal / Remote
Picking the right contraception is an overwhelming task. There is currently no recommender that considers previous methods a person has tried and the side effects they've experienced. I used unsupervised machine learning to build a personalized recommendation model and deployed the app on Heroku, which I will be demoing in my talk.