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Hi there, I am Abheesht 👋

I'm an Applied Scientist at Amazon Science. I work in the Traffic Quality team, where we devise Machine Learning techniques to detect advertisement bots. I love contributing to open source and have been contributing extensively to KerasNLP.

Connect with me:

abheesht17.github.io/

penstrokes17 | Twitter

sharmabhee@gmail.com | E-mail

abheesht-sharma-567303156 | LinkedIn

Abheesht's Projects

applied-ml icon applied-ml

📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

biomedical icon biomedical

Tools for curating biomedical training data for large-scale language modeling

code-soup icon code-soup

This is a collection of algorithms and approaches used in the book adversarial deep learning

decepticonlp icon decepticonlp

Python Library for Robustness Monitoring and Adversarial Debugging of NLP models

drift icon drift

DRIFT is a tool for Diachronic Analysis of Scientific Literature.

keras-core icon keras-core

A multi-backend implementation of the Keras API, with support for TensorFlow, JAX, and PyTorch.

keras-io icon keras-io

Keras documentation, hosted live at keras.io

keras-nlp icon keras-nlp

Industry-strength Natural Language Processing workflows with Keras

lillie icon lillie

OIE Triple Extractor for Database Integration

models icon models

Models and examples built with TensorFlow

promptsource icon promptsource

Toolkit for collecting and applying templates of prompting instances

recam icon recam

Our repository for the code, literature review, and results on SemEval-2021 Task 4: Reading Comprehension of Abstract Meaning

sktime icon sktime

A unified framework for machine learning with time series

super-pixels icon super-pixels

Code for our paper: Superpixel-based Domain-Knowledge Infusion in Computer Vision (https://arxiv.org/abs/2105.09448)

transformers icon transformers

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

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