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This repository implements N-gram language modeling with Kneser-Kney and Witten Bell smoothing techniques, including an in-house tokenizer. It also features a neural model with LSTM architecture and calculates perplexities for comparing language and neural models.

Python 100.00%
kneser-ney-smoothing language-model lstm n-gram-language-models neural-models python witten-bell

language-modelling-and-smoothing-techniques's Introduction

Hi 👋, I'm Aakash Tripathi

I am an MTech CSE Student at IIIT Hyderabad(2022-2024) keen on learning Efficient Computer Science Algorithms, building efficient and scalable systems and Data Exploration by leveraging ML/DL algorithms. I am passionate about different domains in Computer Science and exploring them.

akash18tripathi

  • 🔭 I’m currently working with Media.Net as an SDE Intern.

  • 🌱 I’m currently learning High Level Design and Low Level Design and Implementing Machine Learning Algorithms from Scratch for deeper understanding

  • 👯 I’m Constantly Improving on Advance Data Structures and Algorithms

  • 💬 Ask me about Core Computer Science Concepts based on DBMS,Networking,etc..

  • 📫 How to reach me [email protected]

  • ⚡ Fun fact I think I am Noob at everything! :)

Connect with me:

aakash-tripathi-389658172 akash18tripath akash18tripathi @aakash592 akash18tripathi

Languages and Tools:

android bash bootstrap cplusplus css3 docker firebase flask git heroku hive html5 java javascript jenkins kafka linux mongodb mysql nginx opencv pandas postman python pytorch scikit_learn seaborn sqlite tensorflow

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