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Created almost 8 years ago
Updated over 6 years ago

pushpendrapratap

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It uses extensive NLP and ML techniques at its backend for answering descriptive type queries ( currently, the model has been trained only for Data science and Machine Learning Domain ).

Word-Sense-Disambiguation-WSD-system

In this, I have created, trained and evaluated a WSD system using the SENSEVAL corpus based on the vector space model (VSM).

Python

Multilingual-Dependency-Parser-for-English-Spanish-and-Dutch-Language-

In this, I have implemented a form of Joakim Nivre’s “arc-eager transition-based dependency parser”.

HTML

smartcab-using-Reinforcement-Learning

In this, the self-driving agent uses RL techniques in a simplified world (created using Pygame) to effectively reaching its destinations in the allotted time. It uses Q-Learning algorithm to find the best configuration of learning and exploration factors to ensure that it is reaching its destinations with consistently positive results without causing any traffic violations (like traffic light and oncoming traffic at each intersection).

Python

p2p-lending

A decentralized, smart contract based chit fund platform on the Ethereum Blockchain

Solidity

pushpendrapratap/Question-Answering-system-

pushpendrapratap

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