Dave Ramsey Email & Phone Number

Philadelphia, Pennsylvania, United States

a. Support creating, training and monitoring of production level models as requested bythe teamb. Analyze experiment results and configurations and perform tuning and modification toexperiments to improve model accuracy and performancec. Assist with upkeep of the ML Operations Pipeline and the ZeroEyes Network Toolkit andperform associated QA tasksd. Identify areas of focus and interest and pursue projects to enhance the performance ofZeroEyes deep learning models and the ML Team

Philadelphia, Pennsylvania, United States

- Manage and improve our Al development infrastructure.- Optimize environments for training and testing deep learning models.- Build tools to automate manual tasks and visualize experiment data to communicate to the team. - Strategically guide developers and stakeholders as Al SME during new product development. - Develop APIs that enable our Al models to communicate with partners and customers. - Develop scalable testing procedures for evaluating model performance - Develop scalable data pipelines in order to store, serve, and inference of large amounts of data- Integrate augmentation techniques- Implement security measures to protect our models and data pipelines.- Collaborate with the engineering team to deploy models in production.

Philadelphia, Pennsylvania, United States

Volunteer Organizer for Data Science Philly. a community-run group for anyone interested in gaining insights from data. Topics include (but are not limited to) predictive analytics, applied machine learning, big data, data warehousing, and data science. We <3 data!Join our slack to help plan future events! http://bit.ly/DataPhillySlackEmail us at: admin[at]dataphilly.com

United States

Hey, I'm Dave. I have a degree in Jazz Trumpet Performance and I'm a coffee expert, but when the Covid shut down I began learning python. Now I've done over 20 projects scraping websites, using apis, pulling data from AWS using SQL, to NLP Neural Network Machine learning, Image recognition, and price prediction using Random Forests.I'm currently a fellow at Bluebonnet Data in a five person data team. We're helping a state senate candidate use the data available to optimize thier time and energy to connect with the right voters in the best places.

United States

Fellow & Mentor January-August 2022Scraped and wangled valuable election data for candidate in a newly drawn state senate district from local gov. websites.Created signature verification search tool(5x faster) and population density analysis for targeted efficient door knocking.Mentored a team for a completely separate campaign.

New York City Metropolitan Area

● Trained Random Forest Regression (66% accurate) model predicting user longevity (5+ sessions) from most important behaviors (features)● Conducted hypothesis test (p < 0.001) at a 95% confidence level, showing that “following a curator” in a user’s first session reduced the likelihood of becoming a “super-user” (5+ sessions)● Identified error in ETL pipeline where user data was unknowingly split into two different unique ID’s skewing all ML inference

San Francisco Bay Area

● Discovered the key predictive indicators/features for a user's likelihood to subscribe to StrataScratch YouTube channel● Discovered niche client competitors using subscription data pulled using YouTube API● Used NLP topic modeling using Top2Vec to analyze which topics and words were related to popular and unpopular videos