Hannah Igboke's Projects
25 days consistency challenge in writing DAX codes used to analyse data to provide insights.
This is my analysis for the learning data challenge organized by 365 Data Science.
The aim of this project is to develop, design, and build a comprehensive and scalable database system for Olist Store to handle potential increases in data volume and allow for more efficient data collection, retrieval, and organization.
A Retrieval Augmented Generation (RAG) system leveraging the Gemini API to answer questions on the βLeave No Context Behindβ paper published by Google on April 10, 2024.
This project uses HTTP requests to connect with APIs or web servers for essential data tasks in data science workflows, including retrieval, submission, and updating. In this project, I utilize Python, HTML, and Flask frameworks to refactor and fix bugs identified for the Scribble app.
A Conversational AI Data Science tutor, created to discuss only data-related topics and questions.
What are some of the best ways to prepare a large dataset for modeling? In this project, I optimized the memory usage of the dataset to ensure that it is stored as efficiently as possible to allow models to run faster.
A business analysis on Danny's Diner.
This is an exploratory analysis of the EPL soccer data for the 2018β2019 season. Using Python, I identified interesting trends to answer specific questions from the data.
An analysis of workouts by users of the Redmi Fuel band fitness tracker for the month of January
Improve your Python code with GenAI! This AI-powered assistant reviews your code, identifies potential bugs, and suggests fixes to help you write cleaner, more robust applications.
What interesting trends can be seen from the AMEO 2015 study? This is a comprehensive Exploratory Data Analysis of the AMEO study using Python. Come see what I found out during my analysis.
Maven Toys, a toy company is looking to expand their business with new stores. This is a sales performance analysis focused on analyzing interesting patterns and trends in their data to help them make informed decisions.
Using descriptive analysis to answer business questions and make recommendations to optimize Pizza Runner's operations and drive sales.
This repository features a four-pronged, in-depth investigation into global video games sales between 1980 and 2016.
This is a Regex Matching web app that allows users to input a test string and a pattern (regular expression) to search for and displays the number of matches and all the matches found.
Leveraged natural language processing and machine learning techniques to enhance the relevance and accuracy of search results by building a semantic search engine.
Integration of a trained sentiment classification model into a Flask web app for real-time inference on product reviews from Flipkart store.