Discover @AnjaneyaTripathi Open Source projects

Anjaneya Tripathi (@AnjaneyaTripathi)

AnjaneyaTripathi

Stars
150
Global Rank 153,752 (Top 6 %)
Followers 114
Following 114
Registered about 6 years ago
Most used languages

Python
33.3 %

Jupyter Notebook
25.0 %

JavaScript
16.7 %

CSS
8.3 %

EJS 8.3 %

Yacc 8.3 %
Location 🇮🇳 India
Country Total Rank 4,190
Country Ranking

Yacc 1

Jupyter Notebook
461

EJS 996

JavaScript
4,394

Python
5,549

CSS
9,253

c-compiler

A compiler that accepts any valid program written in C. It is made using Lex and Yacc. Returns a symbol table, parse tree, annotated syntax tree and intermediate code.

knowledge_graph

Knowledge Graph for Legal Documents using Litigation Releases from the SEC website. Classifies into different crimes, extracts relevant information (violator, violation, action taken by authorities and fines) and finally generates the knowledge graph.

Jupyter Notebook

ontology-knowledge-graph

A basic implementation of ontologies and knowledge graphs.

Jupyter Notebook

wordle-solver

Chrome extension for the game called Wordle. No need to get stuck again while you have this at your side. Climb up that leader board!

cricket_updates

Allows you to get updates about the latest cricket matches in your terminal as well as WhatsApp

ORuML_implementation

Identifying the optimal route in a network using machine learning and neural networks

dump

Tech Projects and Notes

Jupyter Notebook

multilingual-summarizer

A multilingual and multi-document model that uses an enhanced version of TF-IDF and knowledge graphs to generate an abstractive summary

technical-questions

A collection of questions on various technical topics.

pyEducate

A portal in Flask using natural language processing (NLTK and spaCy) to provide new methods for students to learn. Helpful for last minute preparations (summarization and questions) and for visual learners (mind map).

shopSmart

A website that allows you to browse through a range of products, add them to your cart, place orders and track them. Has two interfaces - one for the customer and the other for the shop owner.

product-review

Get reviews of products based on tweets using state-of-the-art models. Transformers assist in determining the overall sentiment of the product and return realtime reviews.