About | My projects

Current Projects

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Previous Projects

My GitHub contributions:

Harshit's Github chart
  • DCGAN face generation Mar 2019
    Implemented DCGAN (Deep convolutional generative adversarial networks) for human face generation.
  • ImageCaptioner: Image captioning using Encoder-Decoder Jan 2019 - Feb 2019
    Developed image captioning application based on Neural Image Caption model utilizing encoder-decoder architecture, using pretrained CNN as encoder and LSTM as decoder.
  • Style Transfer in PyTorch Dec 2018
    The style transfer implementation of Image Style Transfer Using Convolutional Neural Networks by Leon A. Gatys et al. in PyTorch.
  • Plant Disease Detection and Recognition Aug 2018 - Sep 2018
    Used Transfer Learning to develop a plant disease detection and recognition system. Applied ResNet101 architecture of Convolutional Neural Networks in the model. Developed an Android app to display the system
  • TweetSense: Real-time social media sentiment analysis July 2018 - Aug 2018
    Developed an application that analyzes tweets and intelligently provides real-time feedback, using sentiment analysis, in a visual manner with the help of a time series graph. The app also provides the sentiment analysis of tweets in the last week. TweetSense also analyzes user's text and provides tone analysis (using Watson API) in addition to sentiment score.
  • Railway ticketing system Apr 2018
    Developed a desktop app in Qt (C++ cross-platform framework) for railway ticketing system.
  • DengueApp: Location based dengue prediction Jan 2018 - Mar 2018
    Developed an Android app that gives real-time location-based dengue risk index to the user using machine learning techniques. The model used the weather conditions of the user’s location as features. The gradient boosted trees performed better than other algorithms. Hosted the model on Django server as an API. Showed the application at Smart India Hackathon 2018 grand finale.
  • Housing price prediction Jan 2018
    Predicted housing price using regression techniques. Applied different models (linear regression, Lasso, Ridge, boosting, random forest). xgboost outperformed other models.
  • Titanic survivors Oct 2017
    Predicted survival on the Titanic using machine learning techniques. Tried different models (SVM, kNN, logistic regression, random forest); random forest gave the highest accuracy.
  • Technical Fridays - personal website and blog July 2017
    This is my personal website and blog developed with HTML5, CSS and JavaScript using Jekyll and Github pages.
  • Blog in django March 2017
    A blog developed in Django, a high-level python web framework using PostgreSQL database.
  • python-projects Feb 2017
    It is a series of small programs written in python.

Conferences

  • PyData Delhi 2018Aug 2018
  • Fourteenth Annual IFIP WG 11.9 International Conference on Digital Forensics, DelhiJan 2018

External Events

  • NVIDIA Developer Connect, DelhiSep 2018
  • Rajasthan Hackathon 5.0, Bikaner.July 2018
  • Google Cloud Summit 2018, Delhi.Jun 2018
  • Smart India Hackathon grand finale 2018, Pune.Mar 2018
  • Rajasthan Hackathon 4.0, Jaipur.Mar 2018
  • Kaggle SQL Scavenger Hunt.Feb 2018
  • Competitive programming competition at tech fest TECHSURGE, MAIT, Delhi.Mar 2017
  • The 5th International Young Mathematicians Convention (IYMC), CMS, Lucknow.Dec 2012
  • National Mathematics Convention, All India Ramanujan Maths Club, Science city, Ahmedabad.Oct 2012