👩🏽‍💻 I am a Software Engineer and an open-source contributor with a focus on backend engineering and experience in developing full-stack web applications and chatbot applications utilizing Machine Learning.

🌱 I enjoy being challenged and engaging with projects that require me to work outside my comfort and knowledge set, as continuing to learn new languages and development techniques are of high value to me.

🎯 I am keen on taking challenges and making the most of the opportunities where I can put my abilities to work for a mission I am passionate about.

💡 Being a self-learner and researcher, I love tackling real-world problems by building technological solutions and have only driven to optimal solutions.

🚀 I am ready to take the next step where I can continue to grow and use the skills that I have honed in my academic and professional experience.

PinnedLoading

1. tech-forecast-1tech-forecast-1Public

   Full stack web application for exploratory data analysis and demand forecasting to aid technology-based choices using Stack Overflow data using Prophet. This application allows users to review info…

   Jupyter Notebook 2

2. react-app-socatrareact-app-socatraPublic

   This web application calls the Socrata API and displays a table and visualizes results via Pie chart about Seattle Food Establishment inspections.

   JavaScript 1

3. Transfer-Learning-COVID-19Transfer-Learning-COVID-19Public

   CMSC-678-ML-Project : Detection of COVID-19 in Pneumonia-affected Patients using Chest X-Ray Images with Transfer Learning

   Jupyter Notebook 9 5

4. Machine-Learning-PerceptronMachine-Learning-PerceptronPublic

   Implemented a Single Layer Perceptron and applied it on MNIST dataset for multi class classification

   Jupyter Notebook 2

5. ML-Neural-NetworksML-Neural-NetworksPublic

   Designing an Artificial Neural Network for Multi-class classification of MNIST data using NumPy.

   Jupyter Notebook 2

6. RegressionRegressionPublic

   CMSC Data Science Project to study various trends and impact of weather conditions on energy consumption by implementing a Linear Regression model to predict consumption in the City of New York .

   Jupyter Notebook 2