I love to write poems, tell stories and play games. Poems about people. Stories about graphs. Games about the unreal.
Since you are already on my portfolio, you will get to know everything regarding my technical skills and interests. So I'll tell you something you won't find on my resume. Well then, I'll tell you how I initially made friends in college. You see, people love talking about themselves and get excited when someone says that they would like to write something for them. And that's exactly what I did. I strike up a conversation and then let them know that I'd love to write a poem for them if they could tell me somethingthemselves. I take what they tell me, write a poem using the information and we become friends. I still think it should not have worked. But, it works so it works, I guess? And it helps a lot when you are trying to understand the other person.
Statistical analysis of 12 datasets for each month of the year 2019 was done. They were combined into one dataset, preprocessed, and engineered to help us answer insightful questions about the data.
Analysis of the Wisc-bc-data from kaggle on a jupyter notebook. Feature engineering and statistical analysis was performed. Machine learning algorithms were employed to detect the type of cancer.
Detection of the severity of heart failure in patients using artificial neural networks. Keras was used to create the neural networks. The model was trained for 100 epochs and then the accuracy was checked.
A dataset with information about people was taken and analysed to predict whether the person would earn greater than or less than 50,000 USD (Hopefully a month) or not. The inconsistent data needed a lot of preprocessing.
Built a Covid-19 Tracker in India with a friend over one weekend and hosted it on the web. We scraped the data from https://www.mohfw.gov.in/ and used it to get information on the active and recovered cases along with the fatalities.
A Python command line app (CLI) that installs all required modules to any python environment with the help of the OS and Sys module. The user's desired domain, locations and environments can be specified at execution time using the argparse library.
The statistical analysis of the Iris dataset is performed using the pandas library in Python. Seaborn is used to plot the graphs. Machine Learning models and ensembling models are used to predict the species of the Iris flower. The notebook is hosted on github.
As a data analyst intern I was first trained in the basics of python, mathematics and statistics and finally the anaconda distribution system. I also worked on multiple real-world datasets and built machine learning models to solve the problem statement after exploring the data.
As a core team member of codezoned, I've had the opportunity to lead the Web dev team to build the official Codezoned website. I've also contributed to multiple other projects in codezoned like the Github Auto-inviter and led the tech team in the HAC2020 hackathon with MLH and Github.
Built a GST Billing website, complete with an Admin panel using HTML, CSS, jQuery, AJAX, and PHP. The website features products, accessories, details of clients, suppliers, and manufacturers, along with billing information, billing and database management and storage. A dummy repo is linked here.