Data Science Project Archive
Explore my diverse and dynamic repository of new projects, offering a practical showcase of data science. With detailed case studies, project breakdowns, and insights into various techniques and methodologies, it’s a treasure trove for those keen on the practical application of data science and analytics. Dive into my work in machine learning, natural language processing, data visualization, and predictive analytics. Each project, complete with comprehensive explanations, code snippets, and visualizations, offers a clear window into my approach to solving real-world data challenges.
2025
Building a Comprehensive Data Validation and Reporting Tool with Python
In a world driven by data, maintaining data quality is essential for informed decision-making. Whether it’s analyzing student records, financial data, or operational metrics, inconsistencies in data can lead to incorrect insights. To address these challenges, I developed a Data Validation and Reporting Tool that automates quality checks, ensures compliance, and provides clear, actionable insights through detailed reports. Continue reading Building a Comprehensive Data Validation and Reporting Tool with Python
2024
Project Overview
In today’s data-driven education environment, effectively managing and analyzing student data is paramount. My recent work on a Python-based Student Data Analysis System showcases my expertise in building scalable solutions that streamline data processing, visualization, and reporting. This blog highlights the system’s design, features, and the value it brings to educational institutions. Continue reading Project Overview
2023
Human Resources Data Analysis
In this project, we embark on a journey of HR Analytics to analyze and visualize our company’s extensive dataset. Continue reading Human Resources Data Analysis
2021
General Outline
In this project we will construct a recurrent neural network for the purpose of determining the sentiment of a movie review using the IMDB data set. We will create this model using Amazon’s SageMaker service. In addition, We will deploy our model and construct a simple web app which will interact with the deployed model. Continue reading General Outline
Get the Data
In this project, we will define and train a DCGAN on a dataset of faces. Our goal is to get a generator network to generate new images of faces that look as realistic as possible! The project will be broken down into a series of tasks from loading in data to defining and training adversarial networks. At the end of the notebook, we will be able to visualize the results of our trained Generator to see how it performs; our generated samples should look like fairly realistic faces with small amounts of noise. Continue reading Get the Data
Predicting Landmark Duration
Photo sharing and photo storage services thrive on location data for the images uploaded by their users. Location data enables useful features like automatic tagging suggestions and organization of photos, greatly enhancing the user experience. However, many uploaded photos lack location metadata due to reasons like cameras lacking GPS or privacy concerns removing metadata. Continue reading Predicting Landmark Duration
Load and prepare the data
In this project, we will build a neural network and use it to predict daily bike rental ridership. Continue reading Load and prepare the data
Get the Data
In this project, we will generate your own Seinfeld TV scripts using RNNs. We will be using part of the Seinfeld dataset of scripts from 9 seasons. The Neural Network we will build will generate a new ,fake TV script, based on patterns it recognizes in this training data. Continue reading Get the Data
2020
Reading data for preprocessing
This project involves implementing various models and performing preprocessing on the data to compare the results and performance of different models. We applied statistical techniques to see which model is performing best. In this project, we will create a binary classifier that predicts whether a data scientist will remain a USDU member or not. Continue reading Reading data for preprocessing
2019
Identify Metastatic Cancer
In this project, we develop an algorithm to identify metastatic cancer in small image patches taken from larger digital pathology scans. The data for this competition is a slightly modified version of the PatchCamelyon (PCam) benchmark dataset. The original PCam dataset contains duplicate images due to probabilistic sampling; however, the version presented on Kaggle does not include duplicates. Continue reading Identify Metastatic Cancer
Women’s Clothing E-Commerce Reviews
This study aims to assist the e-commerce company in developing a machine learning model that can automatically assess customer feedback to determine whether a product is recommended Continue reading Women’s Clothing E-Commerce Reviews
