Apply predictive analytics and statistical modeling techniques to assess surveys for key drivers as they relate to outcomes.
Apply predictive analytics and state of the art Natural Language Processing techniques to improve both employee (micro) and company-wide (macro) infrastructure.
Apply predictive analytics and state of the art Natural Language Processing techniques to improve both employee (micro) and company-wide (macro) infrastructure.
Design web scrapers and fully connected APIs to collect and display pro cycling statistics
and schedules across various levels of professional road and gravel cycling.
Frameworks & concepts:
Apply computer vision and image processing techniques to successfully detect lane lines from a forward facing
dash cam.
The F-MNIST dataset consists of 60,000 black and white images of clothing, all of 28x28 resolution.
Use multi-class classification techniques to accurately classify images of clothing.
24,000 row, 13 column dataset consisting of various
parameters including median house price, median size, number of bedrooms,
median income, etc.
Each sample is a district (block) consisting of anywhere between 20-400 homes.
Dataset parameters consist of averages of each district.
Clean and analyze all data. Find emerging trends in housing and why these trends
may or may not persist.
Techniques included:
