Anmolika Singh
Data Scientist at Stanley Black & Decker
Expertise: Machine learning, Python, R and data analytics
Education: The Pennsylvania State University
Anmolika Singh is a data scientist for Stanley Black & Decker. She’s an experienced data scientist skilled in machine learning, Python, R and data analytics. Singh earned her bachelor’s degree from The Pennsylvania State University.
Sort By
Most Recent
6 Articles
Data lineage tracks how data moves and transforms across systems. Learn how it supports governance, observability and regulatory compliance.
AI governance is a collection of frameworks, policies and ethical guidelines that guide the ethical development and deployment of AI. Here’s what to know.
Data abstraction is a technique that hides intricate implementation details while spotlighting only essential functionalities. Here’s what you need to know.
The Gale-Shapley algorithm is a deferred acceptance algorithm used in matching theory to solve the Stable Marriage Problem. Here’s how it works and how to apply it in Python.
Power analysis is a process that involves evaluating a test’s statistical power to determine the necessary sample size for a hypothesis test. Learn more.
Agent-based modeling (ABM) is a computational modeling technique that mimics how an individual agent behaves with an environment to simulate the overall system behavior. Here’s what to know.