2271 results for "earn" across all locations
Nobody knows the ins and outs of using the Uber Driver app better than you. So when we set out to build a better app experience, we asked for you help
The Top 5 Farmers Markets in Toronto
Budgeted Training: Rethinking Deep Neural Network Training Under Resource Constraints
M. Li, E. Yumer, D. Ramanan
Current approaches for hyper-parameter tuning and neural architecture search tend to be limited by practical resource constraints. Therefore, we introduce a formal setting for studying training under the non-asymptotic, resource-constrained regime, i.e. budgeted training. We analyze the following problem: “given a dataset, algorithm, and resource budget, what is the best achievable performance?” [PDF]
International Conference on Learning Representations (ICLR), 2020
Maximum Relevance and Minimum Redundancy Feature Selection Methods for a Marketing Machine Learning Platform
Z. Zhao, R. Anand, M. Wang
In machine learning applications for online product offerings and marketing strategies, there are often hundreds or thousands of features available to build such models. Feature selection is one essential method in such applications for multiple objectives: improving the prediction accuracy by eliminating irrelevant features, accelerating the model training and prediction speed, reducing the monitoring and maintenance workload for feature data pipeline, and providing better model interpretation and diagnosis capability. […] [PDF]
IEEE International Conference on Data Science and Advanced Analytics (DSAA), 2019
Step out of the city with UberIntercity
Step out of the city with UberIntercity
Collaborative Multi-Agent Dialogue Model Training Via Reinforcement Learning
A. Papangelis, Y.-C. Wang, P. Molino, G. Tur
We present the first complete attempt at concurrently training conversational agents that communicate only via self-generated language. Using DSTC2 as seed data, we trained natural language understanding (NLU) and generation (NLG) networks for each agent and let the agents interact online. […] [PDF]
Special Interest Group on Discourse and Dialogue (SIGDIAL), 2019
Learnings in Web Development: Design Patterns, Elm, and Progressive Enhancement
Uber’s Destination:Web meetup series gives great insight about the most current web building tools and techniques. These three videos from Uber presenters offer tips on a mysterious design pattern, the Elm language, and Progressive Enhancement.
Learn how Uber Freight is helping United Reuse grow its business
Thanks to Uber Freight’s instant quotes, the industrial packaging company now saves hundreds of hours in booking time.
5 key learnings from Uber’s leadership panel on the power of visibility
To celebrate International Women’s Day, we hosted a panel of leaders from across Uber showcasing the power of visibility. Ana Loibner, Global Mobility Chief of Staff and Women at Uber Global Board Member, shares what she learned.
