Project Information

Project Description

This capstone project is one of our final requirements for the degree BS in Data Science. We directed our study to deep learning specifically on image processing. The goal of this study is to help local rice farmers not just identify the manifesting rice disease on their rice crops but to assess the severity of the manifesting disease. The entirety of the program works as expected however it is yet in its prototype phase.

Project Information

Project Description

Our project focused on querying food product-related incident data from the US government API called OpenFDA. We performed data wrangling to clean and organize the data, and then derived insights from it. Our goal was to gain a deeper understanding of food safety issues and contribute valuable knowledge to the field.

Project Information

Project Description

In this project, we classify textual data using traditional machine learning classification models. Our data were queried from an API about hotel reviews. We implemented different procedures for text preprocessing like Bag of Words and term frequency-inverse document frequency, we also did tokenization, lemmatization, stemming and other preprocessing technique.

Project Information

Porject Discription

This is our final project for the course Machine Learning. The data were downloaded from kaggle. Prior to machine learning implementation, we first performed exporatory data analysis and hypothesis testing to examine the data and its features.

Project Information

Project Description

This is one of our projects in Machine Learning, this is about predicting mobile phone price range using regression models. Just like other machine learning, we implemented data preprocessing prior to training the machine learning models.

Project Information

Project Description

This is our final project in the course Deep Learning, in this project we obtained our image data through web scraping, we then used pre-trained object detection model specifically YOLO-v5 to detect the objects of interest which are vehicles. We then experimented on fitting the data to different CNN models to classify whether a vehicle is an emergency vehicle or not.

Project Information

Project Description

SmplML is a user-friendly Python module for streamlined machine learning classification and regression. It offers intuitive functionality for data preprocessing, model training, and evaluation. Ideal for beginners and experts alike, SmplML simplifies ML tasks, enabling you to gain valuable insights from your data with ease.

Project Information

Project Description

Time Series Binder is a Python library for time series analysis and forecasting. It provides a comprehensive set of tools and models to manipulate, visualize, and predict time series data. This library is designed to assist researchers and analysts in performing various time series tasks with ease and efficiency.