Akriti

Applied Science, Search and Relevance. Microsoft. #WomenInSTEM

[Anthony Goldbloom @antgoldbloom]

Wonder what the impact of ChatGPT is on StackOverflow SO.

Six months ago, I didn't go a day without visiting SO. Now I find ChatGPT almost always answers my coding questions accurately (and much faster and with more directly applicable code examples).

[Akriti @akriticodes]

Having #migraines is a very expensive chronic illness is what I’m understanding with every passing day. 🫠

[Akriti @akriticodes]

Wordle 215 3/6

⬛⬛⬛⬛🟩
🟨🟩🟨⬛🟩
🟩🟩🟩🟩🟩

I guess we are doing this in public starting today. 😂🥲

[Akriti @akriticodes]

@KARTHIKRK94 @qatarairways The ticket that was cancelled has the flight on Feb 6.

[Akriti @akriticodes]

Anybody recently faced an issue with @qatarairways ?? They cancelled a scheduled ticket without prior notice (the flight is still scheduled), sent refund to the credit card, and now expect me to book the same ticket for double the price?????????

[Akriti @akriticodes]

@qatarairways #help

[Akriti @akriticodes]

Anybody recently faced an issue with @qatarairways ?? They cancelled a scheduled ticket without prior notice (the flight is still scheduled), sent refund to the credit card, and now expect me to book the same ticket for double the price?????????

[Akriti @akriticodes]

@redcat9 Time to break up with the coffee shops

[Akriti @akriticodes]

Day 12 : A machine learning algorithm’s interpretability refers to how easy it is for humans to understand the processes it uses to arrive at its outcomes. Until recently, artificial intelligence algorithms have been notorious for being “black boxes,” but hopefully not for long

[Akriti @akriticodes]

I’m going to use this thread and populate it with my daily progress for #100DaysOfML. Does @TwitterEng allow support for 100 tweets in a thread? 🤪 we’ll see how this goes! 👇🏻🔻

[Akriti @akriticodes]

Day 9 : moved over to perceptrons. A Perceptron is an algorithm used for supervised learning of binary classifiers. Sooo the inductive bias of a perceptron is that it has a linear classification boundary 🤭 I’m in a little bit of a slump. My reading list is increasing 🤷🏻‍♀️

[Akriti @akriticodes]

Day 11 : I did nothing exciting. The chapter from which I read boosting also@had an introduction to bagging, Amd ensemble methods in general. I spent some time reading it up and brushing my basics. But what I am REALLY interested in is gradient boosted decision trees.

[Akriti @akriticodes]

Day 10 : I “tried” to study boosting - and I call it tried because I only understood a little bit of adaboost and a little bit of gradient boost. I, however, understand the concept of putting weak learners sequentially to build a stronger learner.

[Akriti @akriticodes]

#100DaysOfCode #100DaysOfML

[Akriti @akriticodes]

Day 4 : visual guide to information theory and regression trees for the day! 🙀 @statquest to the rescue 🏀

[Akriti @akriticodes]

#100DaysOfCode #100DaysOfML

[Akriti @akriticodes]

Day 3 : Entropy and Information gain with @tommmitchell 😅 I spent a couple of more hours reading the book chapter + talk about decision trees and how to split most precisely. Didn’t get to overfitting yet because an hour and a half at 11 in the night is exhausting