Finding parking in busy cities is stressful. Out of a sample of drivers in Seattle, 83% stated that they prefer public street parking to paid garages or lots, citing the significantly lower cost-per-hour and proximity to their intended destination. However, repeatedly circling an area for parking creates anxiety, increases traffic congestion, and pollutes the environment; consuming both time and gas. Gradient aims to streamline the street parking experience by leveraging civic parking data, crowdsourced user-input, and machine learning to predict the availability of nearby public street parking in real-time.

National surveys show the majority of Americans have used an app to track anything related to their health. Unfortunately, almost half of those users have deleted those apps due to lost interest or time wasted entering data. Using Clarifai, an established machine vision company, HealthNuts has created a mobile friendly web application that allows people to simply take a picture of the foods they eat to record and display the nutrients they receive. This avoids the time and effort required for tracking this information by hand and creates a fun and unique experience to help people reach their nutritional goals.

Test Innovators is a firm that helps young students prepare for standardized tests like ISEE and SSAT and is looking at ways to develop a recommendation system that can be leveraged to improve their performance in tests. This project will entail identifying an exhaustive series of areas where a test-taking student is not performing well and recommending resources that will lead to the student’s improvement. The focus will be on developing an algorithm, which caters to this business requirement. The project aims to help the students improve on their weaker domains and take their first step towards a bright future.

With 345+ data points on 920,000+ companies worldwide PitchBook provides the industry's most comprehensive M&A, PE and VC database and analysis Platform. However, there is no accurate prediction of a company’s potential growth or logical, unbiased correlation between the many data points that will aid in decision-making process. Team Infoception performed extensive data research and analysis, and designed a visualization prototype that will provide needed insights to PitchBook’s customers. This dynamic, interactive dashboard provides unbiased insights based on user preferences and will hugely benefit PitchBook users to easily access, understand, compare and convert data to relevant, well-informed decisions.

Pitchbook enables client decision making by tapping into the power of data, available technology and market research, Pitchbook provides its clients with a News Feed section to provide current and consolidated news. However, the Company wanted to go a step further and provide customized news as opposed to several irrelevant articles that are surfaced in the News Feed. Our News recommendation engine allows us to affect more than 25,000 interactions a day on the Pitchbook platform by surfacing customized and relevant news articles using a combination of data science and topic modelling techniques

Understand relationships between stock movement and social media sentiment in the company's Twitter posts is appealing and catching attentions of both academic and industrial researchers  nowaday. One of the factors preventing their analysis from great accuracy is the quality of the text data and how to mine it. Our team want to examine some of current models (Logistics, Naïve Bayes and CNN) to mine text data, specifically for enterprises’ tweets. Our research question is: To mine data from companies’ tweets in Twitter, which one is the best method to build a tweet sentiment analysis model with limited supervised data?

Interoperability, dispersed data, and inconsistent data formats are common issues across information science. This Open Data Literacy (ODL) Capstone tackles these issues in the realm of environmental restoration. Numerous restoration projects have been undertaken throughout the Puget Sound, but connecting investments in these projects to co-located indicators of habitat viability is challenging. Our team leveraged open, found data and open-source tools to build a scalable, sustainable data processing pipeline and an interactive, web-based visualization prototype. This helps our partners better tell the story of Puget Sound restoration efforts and demonstrates that open-source tools can help data curators meet open-data needs.

Data science is changing the face of the financial industry. Visible in the rise of quantitative funds, AI managers, and high frequency trading, 21st century technologies have produced unprecedented volumes of financial data. Without context or a way to capture the big picture, even the most engaged investors are getting left behind. Pariity takes technical, quantitative, and sentiment analysis and makes it accessible and digestible for everyone. We provide a holistic view of markets so that all investors can educate themselves, validate their thinking, and increase their confidence in trading.