Parul Pandey
Machine Learning Engineer at Weights & Biases
Expertise: Data science, machine learning, artificial intelligence
Education: National Institute of Technology Hamirpur
Parul Pandey is a machine learning engineer at Weights & Biases, a developer-first MLOps platform. Before this, she worked as a data scientist at H2O.ai, combining data science and developer advocacy in her work. She is also a Kaggle Grandmaster in the notebooks category and was one of LinkedIn’s Top Voices in the software development category in 2019.
Pandey is co-authoring a book on responsible AI and has written multiple articles focused on data science and software development for various publications. She also has a background in electrical engineering.
Sort By
Most Recent
10 Articles
A vector norm is a function that measures the size or magnitude of a vector by quantifying its length from the origin. Vector norms are an important concept to machine learning. This guide breaks down the idea behind the L¹, L², L∞ and Lᵖ norms.
Pandas DataFrames can be sorted by column, index, multiple columns and more. This tutorial introduces you to the basics.
Trying and failing to decipher your own codebase? Remember: Good code is its own best documentation.
Here are a few important caveats to keep in mind when you’re encoding data with pandas.get_dummies().
Here’s how to heat up your heat maps and make sure they stand out.
Read data directly from the clipboard without saving it first. Here’s how.
Come with me on a whirlwind tour of 5 libraries that will be a great addition to your data science stack.
This open-source Python development framework can help you quantify and eradicate unconscious bias in job descriptions.
Jupyternotify is a Jupyter Notebook extension that provides a browser notification when a code cell is done executing.
Image processing in Python involves using Python to analyze and manipulate digital images to improve quality or extract information. Here’s an overview of common Python libraries used for image processing tasks.