arushi04/character-level-rnn

This project trains a few thousand names from 18 languages of origin and predicts which language a name is based on the spelling. It uses a character-level LSTM model to predict the next character. The model reads words as a series of characters and outputs a prediction and a “hidden state” at each step, feeding its previous hidden state into each next step. We take the final prediction to be the output, i.e. which class the word belongs to.

Hi! I am Arushi 👋

I am a graduate student pursuing Masters in Data Science from Northeastern University, Boston. I have worked in the industry for over 5 years in the field of Data Engineering, Cloud and DevOps. I love to learn new technologies and explore as much as I can! I am currently learning Deep Learning. My area of interest lies in Deep Learning and NLP. My current status:

• 🧠 Learning NLP and developing habit of reading research papers.
• 👯 Excited to be a part of an organization who aims to bring people closer!
• 😄 Pronouns: she/her
• 👩‍ Updates : I am happy to share that I just finished my internship with Facebook and had a wonderful experience. And would be joining them full-time soon!

You can find me on:

🏡 website | 🐦 twitter | 👔 linkedin