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Welcome to Darshan Rao's GitHub Account!

About Me

Hi there! I'm Darshan Rao, a passionate data scientist and software engineer with a strong background in machine learning and artificial intelligence. I have a keen interest in leveraging cutting-edge technologies to solve complex real-world problems. My GitHub repositories showcase a collection of projects ranging from machine learning models and data analysis to mobile app development using Flutter.

Skills

  • Languages: Python, C++, Dart, SQL, Java
  • Frameworks: TensorFlow, PyTorch, Scikit-Learn, Flutter
  • Tools: Jupyter Notebook, Git, Docker, Tableau, Firebase
  • Platforms: AWS, Azure, GCP

Connect with Me

Feel free to explore my repositories, and if you have any questions or collaboration opportunities, don't hesitate to reach out to me. I'm always excited to connect with fellow developers and researchers!

Darshan Rao's Projects

airline-management-system icon airline-management-system

This project on Airline Management System is the automation of registration process of airline system. The system is able to provide much information like passenger’s information, criminal’s, list of all passengers etc. The system also allows us to add records when a passenger reserves a ticket. For data storage and retrieval we use MySQL Database. It enables us to add any number of records in our database.

ancient-hand-writtten-recognition-under-data-deficiency icon ancient-hand-writtten-recognition-under-data-deficiency

Ancient Indian Languages OCR: Enhancing handwritten character recognition using Capsule Networks with minimal data - A novel approach leveraging advanced CapsNets to interpret historical texts accurately with only 190 samples per character, addressing the challenge of scarce labeled datasets in preserving cultural heritage.

c_square icon c_square

Application for Real time Covid cases counting

csci-algo-sequence-alignment icon csci-algo-sequence-alignment

This project implements and compares dynamic programming solutions for the Sequence Alignment problem, including a memory-efficient version, providing alignment costs, optimized sequences, performance metrics, and insightful analysis.

hmm-based-part-of-speech-tagging icon hmm-based-part-of-speech-tagging

This project implements a Part-of-Speech (POS) tagger using a Hidden Markov Model (HMM). It includes code for training the HMM on a dataset, creating a vocabulary, and using two decoding algorithms (Greedy and Viterbi) for POS tagging.

little-go-game icon little-go-game

This Go game AI agent is implemented in Python using the Minimax algorithm to play the game of Go. The agent considers various game states and employs strategic decision-making.

named-entity-recognition-with-bilstm icon named-entity-recognition-with-bilstm

This project implements a Named Entity Recognition (NER) system using a Bidirectional Long Short-Term Memory (BiLSTM) neural network. The system is designed to read in a dataset, train a BiLSTM model on this data, and then use the trained model to predict entity tags for unseen text.

urban_clap_app icon urban_clap_app

Service App for hiring local professionals(Urban Clap App) Frontend

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