Associate @ JefferiesPune, India · Pune, India
Advait Lonkar

Welcome to my personal space for personal & professional growth. Here you will find a mix of technical insights, some personal stories and various other topics that pique my interest.

Currently

  • Cloud and data engineering at Jefferies
  • Writing on Azure, AI, and career growth
  • Distance running, currently training for a half marathon

Recent posts

0 min read

Learning to program in Rust by building my own shell

Learn about parsing commands, executing own programs and more in Rust.

Rust · Shell
2 min read

Evaluating ML Models: Cross Validation, Confusion Matrix, Bias–Variance

Concise notes on cross validation, confusion matrices, sensitivity/specificity, and the bias–variance tradeoff for practical model evaluation.

Machine Learning · Model Evaluation
5 min read

Statistical Foundations of Machine Learning

Notes on mutual information, least squares, linear regression, R^2, F-statistics, p-values, multiple regression, t-tests, and ANOVA.

Machine Learning · Statistics

Projects

Tradezi: A virtual trading application

Tradezi: A virtual trading application

Tradezi is a virtual trading platform that allows users to invest in real stocks with virtual money, facilitating learning of market trends and strategies while showcasing a complete DevOps pipeline implementation.

Learn more
The Physics Hub

The Physics Hub

The Physics Hub is an open source physics simulations project that was developed by physics students worldwide and aimed to deliver clear and easy to understand physics simulations free for everyone!

Learn more
Discussion Analyzer for a Precision Learning Portal

Discussion Analyzer for a Precision Learning Portal

In the Precision Learning Portal project, developed a scalable, personalized social learning platform by creating a user interface (UI) including essential functionalities such as question and answer fields, upvote options, and tools for Teaching Assistants (TAs) to verify content. Implemented APIs to assess discussions and manage inactive threads, along with scripts to utilize data for model retraining and identify potential interveners.