PrinceĀ Grover
Applied Scientist at https://aws.amazon.com/
New Haven, Connecticut, United States
Summary
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RockstarPrince Grover is an Applied Scientist with eight years of experience, currently driving research and production ML work at Amazon from New Haven, Connecticut. He focuses on interpretable machine learning, evidenced by his open-source notes and deep dives into Random Forest confidence intervals and feature importance. Prince blends hands-on model analysis with practical data-science communication, making complex model behaviors accessible to engineers and stakeholders. His GitHub contributions emphasize pedagogy and reproducible insights rather than flashy projects, signaling a preference for clarity and long-term team impact. Colleagues can expect a thoughtful researcher who pairs strong applied skills with an emphasis on interpretable, trustworthy models.
8 years of coding experience
Stackoverflow
59reputation
3kreached
0answers
1question
Github Skills (8)
machine-learning10
random-forest10
feature-selection10
data-analysis10
heatmap6
ggplot6
r6
overlap6
Programming languages (6)
Github contributions (5)
groverpr/Machine-Learning
Nov 2017 - Mar 2020
Notes for machine learning
Role in this project:
Data Scientist
Data ScientistContributions:1 review, 45 commits, 1 PR in 2 years 5 months
Contributions summary:Prince's commits provide notes and explanations on machine learning concepts and techniques. They are focused on understanding Random Forest results including Confidence interval and Feature importance, and they also provide insights on Interpretetion of RF. The commits showcase notes in lectures on key aspects of Random Forest interpretation, helping model understanding and data analysis.
notesmachine-learningdata-science
groverpr/groverpr.github.io
Feb 2020 - Mar 2023
My ML blog
Contributions:7 PRs, 34 pushes, 1 branch in 3 years 1 month
machine-learningdata-science
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