Hi! Glad you are here
I'm Jana Palanisamy , a graduate student at San Jose State University skilled in Python, JAVA and Machine Learning Algorithms. Get in touch janahari23@outlook.com
I'm currently pursuing a Master of Science in Software Engineering at San Jose State University. I belong to India, where I finished my bachelor's degree in Software Engineering from SRM Institute of Science and Technology. After my bachelor's degree, I interned at TekAfforde Solutions Pvt.Ltd a Bangalore-based start-up where I had the opportunity to experience various state-of-the-art business automation, software development, and outsourcing services.
As a software engineer and Data science enthusiast, I enjoy bridging the gap between engineering and data — combining my technical knowledge with my data-driven analytical mindset, I like to find meaningful patterns, reliable, and accurate insights from data to add values to businesses and society.
When I'm not in front of a computer screen, I'm probably with a soccer ball, gardening or crossing off another item on my bucket list. FYI, Played in Soccer Nationals(India). My motto in life 'Surpass your limit. right here,right now'.š
- Python
- JAVA
- JavaScript
- C/C++
- HTML
- CSS
- Scilit-learn
- TensorFlow, Keras
- Pandas, Numpy
- Matplotlib, Seaborn
- Node, React
- RASA
- MySQL, PostgreSQL
- Git & Github
- MongoDB
- Postman
- Anaconda
- SQLite3
- AWS
- GCP
- Docker
- Heroku
- IBM Watson Studio
- Amazon Sagemaker
Designed a smart search recommendation system that can streamline the process of finding potential investments/investors using CrunchBase API and deployed it on Heroku via REST API.
Developed a responsive AI-powered chatbot to handle customer queries regarding food order takeaways. Built using conversational AI platform called RASA. Integrated SQLite3 with python to store and query customer data.
Forecasted store sales on data from CorporaciĆ³n Favorita, a large Ecuadorian-based grocery retailer. Implemented a custom regressor using Ridge and Random Forest models and achieved a competitive RMSLE score of 0.42.
Explored more than 3GB of CRM data and built machine learning pipelines to accurately predict customer churn by 73%, starting from data wrangling, feature engineering, model building, and evaluation using python. Conducted discount-impact analysis to develop optimal discount strategy, increased annual revenue by $60K
Accomplished training classifiers on binary target data for predicting game winners and which team will finish a game with higher stats. Built XGBoost model and tuned hyperparameters to achieve the highest accuracy of 74% with 14.1% macro average gain.
A multiplayer turn based shooting game where 2 players try to hit each other with a physics projectile. This idea came about due to the recent EOLing of adobe flash player. Designed and developed different character models, including more complex multipart sprites. Developed dynamic healthbar visual and dynamic pixel elements imitating snowfall.