Nevin Selby

About Me

Greetings! I am a final year Computer Science student at Indian Institute of Information Technology, Kottayam, who possesses a strong affinity for the fields of Artificial Intelligence, Machine Learning, and Data Science. As a tech-savvy individual, I continuously engage in exploring and experimenting with the most recent advancements in the technology realm.

Currently, I am actively involved in two intriguing projects. One of which entails utilizing Long Short-Term Memory algorithms to predict future stock prices, and the other involves applying Reinforcement Learning to decipher stock market trends. I am fortunate enough to have the guidance of my esteemed supervisor, Dr. Rubell Marion Lincy, throughout these projects.

I am always open to discussing novel and imaginative ideas. If you would like to converse about your latest technical project or simply connect over a virtual cup of coffee, you may reach me at nvnsly@gmail.com.

Latest Projects

Start To End ML

A machine learning project which does data cleaning, EDA, and also provides the best suited model for your data.

This project is designed to provide a comprehensive data analysis solution by integrating three essential processes: data cleaning, exploratory data analysis (EDA), and model selection. Data cleaning helps to ensure the accuracy and reliability of the data by detecting and removing inconsistencies such as missing values and duplicates. EDA is then performed to identify patterns, trends, and relationships within the data, providing valuable insights that can guide decision-making. Finally, the system recommends the best-suited machine learning model based on the results of the EDA, optimizing performance and accuracy. With this approach, users can easily analyze their data, gain valuable insights, and make informed decisions.

Animal Classification Using CNN

I used Numpy, Computer Vision, CNN, and TensorFlow to develop a model that classifies animal images with 76% accuracy. The model learned features of the images using filters and pooling layers, showcasing the potential of combining advanced technologies for efficient machine learning.

WhatsApp Chat Analysis

I used Streamlit, Matplotlib, Seaborn, Numpy, and Pandas to create a web application that analyzes WhatsApp chats. The app provides insights such as the most active user and peak activity time range.

View more of my Work

Work Experience

Data Science Intern - Techolution (Jun 2022 - Aug 2022)

Developed code to extract more than 100,000 book details from various retailers like WH Smith and Amazon.
Used Scrapy, Playwright, BrightData, PIL, and Pyautogui.

Software Development with Python - Aero Telcom Solutions (Oct 2021 - Jan 2022)

Scraped data from different websites and stored it in a precise and structured format.
Used BeautifulSoup4, Selenium, Pandas, Numpy, PIL, and Pyautogui.

Data Science Intern - The Sparks Foundation (Dec 2020 - Dec 2020)

From the given dataset, predicted the scores of students based on how much time they studied.
Used Pandas, Numpy, Matplotlib, Sklearn, and LinearRegression.

Machine Learning Intern - Verzeo (Feb 2020 - Mar 2020)

Given a dataset, predicted the cost of second-hand cars depending on various factors, including the number of kilometers driven, fuel type, mileage, etc. with an accuracy of 93.8%.
Used Pandas, Numpy, Matplotlib, Sklearn, and RandomForestRegressor.

Nevin John Selby

Data Scientist