| [Personal] |
Attention based end-to-end speech to text model: Implemented the Listen, Attend and Spell paper to design a system for speech-to-text transcription using Locked Dropout, Teacher Forcing, and padded Cross-Entropy Loss.
|
| [Personal] |
Machine and Deep Learning framework framework from scratch only using NumPy.
</tr>
|
| [DL research] |
Leveraged the VizWiz dataset (collection of 20,000 images captured by blind people through their mobile phones) to implement MobileNetv3 (CNN model) \& an LSTM based language model to develop a Visual Question Answering based framework. Achieved an accuracy of approximately 60\% using PyTorch library and NVIDIA K80 GPUs on AWS. </a> |
| [ML research] |
Conducted end-to-end data analysis to examine user behavior on Instagram about climate change by using unsupervised clustering techniques on web-scraped images \& associated hashtags. Determined that only ~10\% of all users posted relevant climate change related content between November-December'19.
|
| [Personal-Kaggle] |
Developed an ML pipeline to conduct data-cleaning, pre-processing, feature engineering, \& built 'stacking' ensemble model using Logistic Regression, Support Vector, \& Random Forest classifier to predict survival rate in Titanic Disaster with ~93\% accuracy.
|
| [Personal] |
The aim of the project was to augment enrollment strategy for Udacity. Coducted A/B Testing on a large dataset of students enrolling for *free* courses on Udacity to analyze the effect of 'studytime-filter' on students. Concluded based on statistically significant conversion rate numbers that filter shouldn't be launched.
|
</table>