My GitHub contributions:
Pothole Detection and Segmentation
Jan 2020 - Jun 2020
Fine-tuned custom Mask R-CNN and YOLACT instance segmentation models for real-time pothole detection and segmentation on Indian roads with PyTorch and achieved 86% accuracy, 0.30 mAP on custom testing dataset
Udacity's Deep Analyst Nanodegree projects
Apr 2020 - Jun 2020
- Project 1: Explore Weather trends analyzes local and global temperature data and compare the temperature trends where you live to overall global temperature trends.
- Project 2: Investigate a dataset analyzes a dataset and then communicates the findings.
- Project 3: Analyze A/B test results understands the results of an A/B test run by an e-commerce website.
- Project 4: Wrangle and Analyze Data wrangles and analyzes the tweet data of WeRateDogs that rates people's dogs with a humorous comment about the dog.
- Project 5: Communicate Data Findings deals with data exploration of the flights cancellation and delay dataset mainly using data visualization and present the findings using explanatory visualizations.
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.