My GitHub contributions:
Udacity's Deep Reinforcement Learning Nanodegree projects in PyTorch
Jul 2019 - Nov 2019
- Project 1: Navigation is about training a RL agent to navigate (and collect bananas!) in a large, square world.
- Project 2: Continuous Control is about training a RL double-jointed arm agent so that it can move to target locations.
- Project 3: Collaboration and Competition is about training two RL agents to control tennis rackets to bounce a ball over a net.
Udacity's Deep Learning Nanodegree projects in PyTorch
Dec 2018 - Mar 2019
- Classification: Flower image classification and Dog breed classification
- Generation: TV Script generation and Face Generation using DCGAN
- Deployemnt: Deploying sentiment analysis model on Sagemaker
- Art: Neural Style Transfer
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.
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
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
Predicted housing price using regression techniques. Applied different models (linear regression, Lasso, Ridge, boosting, random forest). xgboost outperformed other models.
- Titanic survivors
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
- Blog in django
A blog developed in Django, a high-level python web framework using PostgreSQL database.
It is a series of small programs written in python.
- PyData Delhi 2018Aug 2018
- Fourteenth Annual IFIP WG 11.9 International Conference on Digital Forensics, DelhiJan 2018
- 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