Deep Learning, Machine Learning and Data Analysis Enthusiast.
Deep learning handles complex and unstructured data, making it ideal for tasks like image recognition and natural language processing. This project using TensorFlow and Convolutional Neural Networks, we trained a model on the image dataset and tested on new images, including cartoon characters and human faces.
This project is to analyze a restaurant's sales data for the past three years alongside the menu, price, quantity sold, and other features. The challenge in this task is to provide insights based on historical data by using data analysis, feature importances and conduct forecasting using regression technique.
I created a recommendation engine for video games using data from the 2023 releases on Steam platform. By extracting metadata like names, features, genres, developers, and descriptions, I trained a collaborative filtering model in Python to recommend games based on user preferences and game attributes.
I analyzed a Kaggle bank dataset to optimize a marketing campaign for user acquisition and cost-efficiency. The project focused on building a machine learning model to predict customer response and recommend cost-effective marketing strategies, addressing key objectives of understanding customer behavior, predictive modeling, and cost optimization.
During my data analysis training, I examined an Airbnb Bangkok dataset from Kaggle to derive actionable business insights. Through comprehensive exploratory data analysis, I focused on enhancing product features, refining pricing strategies, and expanding the range of locations offered to travelers.
For my Python programming capstone, I designed and implemented CRUD system for hospital administration, enabling functionalities for creating, reading, updating, and deleting patient records. In addition, I built another feature for doctor and superadmin role.