Building interpretable Boosting Models with IntepretML — As summed up by Miller, interpretability refers to the degree to which a human can understand the cause of a decision. A common notion in the machine learning community is that a trade-off exists between accuracy and interpretability. This means that the learning methods that are more accurate offer less…

Analyzing the 2021 Abu Dhabi Grand Prix with the Fast F1 library — # First published on Oct 15, 2021. Edited on March 20, 2022 What’s behind you doesn’t matter — Enzo Ferrari The 73rd season of the Formula One World Championship or F1 commenced in Bahrain on 20th March 2022. Fierce battles are being witnessed between the ten teams for the ultimate…

Writing in Data Science can have a transformative effect not only in your journey but also in your career. — I appeared on the FastBook Reading Sessions organised by Weights & Biases to discuss about the benefits of writing in Data Science. I wrote this piece to summarize what I covered there. This article was originally published on their forums but I’m sharing a somewhat edited version here as well…

Infusing Mosaic Magic into Your Plots — Recently, I was working on a project that required creating subplots using the Matplotlib library in Python. If you’ve ever used the Matplotlib library, there’s a high chance you’ve also utilized its subplot functionality. Subplots are an effective tool for generating multiple plots simultaneously, which…

Evaluating single models based on global and local explanations — Machine Learning explainability refers to the ability to understand and interpret the decisions and predictions made by a machine learning model. Explainability is crucial for ensuring the trustworthiness and transparency of machine learning models, particularly in high-stakes situations where the consequences of incorrect predictions can be significant.

Google I/O 2023: A Look at Google's Approach to Building AI Responsibly — It is said that with great power comes great responsibility, but when it comes to the immense capabilities of AI, it brings a whole new level of ethical considerations and accountability. The same sentiment was echoed during Google's much anticipated I/O event on 10th May 2023. The underlying message was…

A framework and no-code GUI designed for fine-tuning state-of-the-art large language models (LLMs). — “Information flow is what the Internet is about. Information sharing is power. If you don’t share your ideas, smart people can’t do anything about them, and you’ll remain anonymous and powerless.” — Vint Cerf While the pace at which Large Language Models (LLMs) have been driving breakthroughs is remarkable, these…

An interview with Lewis Tunstall, co-author of the book- Natural Language Processing with Transformers — A series of interviews highlighting the incredible work of writers in the space of data science and their path of writing. “In fiction, the language and the senses it evokes are important, whereas in technical writing, the content, and the information it conveys, are important.” ― Krista Van Laan, The Insider’s…

An interview with Christoph Molnar, author of the book- Interpretable Machine Learning — A series of interviews highlighting the incredible work of writers in the space of data science and their path of writing. “If you don’t see the book you want on the shelf, write it” — Beverly Cleary In an endeavor to bring such notable work to the forefront, I started…