machine learning

Emotion Detection of r/leaves with HuggingFace and T5

Image Classification using Convolutional Neural Networks, TensorFlow and Keras in Python

Why Convolutional Neural Networks? A Convolutional Neural Network is a Deep Learning algorithm which can take in an input image, assign importance to various aspects in the image and be able to differentiate one from the other. The pre-processing required in a CNN is much lower as compared to other classification algorithms. Why TensorFlow and Keras? TensorFlow is an open-source library for building Machine learning models at large scale. It is by far the most popular library for building deep learning models.

Sentiment Analysis of 2019 Australian Election

I work with a group of Data Scientists, most notably Vinicio Haro from Bloomberg, to perform text mining on over 180,000 tweets during 2019 Australian Election. We implement Sentiment Analysis on tweets to find the overall attitude of the twitter users during the time of election. Then we apply Network Analysis to find Twitter users who are best placed to influence the network and find users who can quickly connect with the wider network.

Recommender System of a Large Dataset in Apache Spark and Python

For this project, I build a recommender system using Alternating Least Squares (ALS) matrix factorization in the cloud (Apache Spark) using R to recommend books based on an individual’s ratings.

Predicting Fraudulent Online Transactions

Applied feature engineering and LightGBM gradient boosting algorithm in Python to detect fraud from customer transactions.