Portfolio

Check Out Some of My Works

NLP Question-Answering AI Web App

NATURAL LANGUAGE PROCESSING

I built and Deployed a Question-Answer NLP model as a Web app using Gradio GUI. I made use of HuggingFace pre-trained model, Gradio GUI, Pandas, and hosted on HuggingFace spaces. Link to App , Github Repository , My article on medium .

Dog Breed Identification

DEEP LEARNING CLASSIFICATION USING TENSORFLOW

This is a project i did which was a competiton hosted by KAGGLE.. it involves using deep learning model to predict and determine the Breed of a dog in a picture, i made use of tensorflow and Keras, numpy, pandas and other libraries.

Predicting Heart Disease using Machine Learning

MACHINE LEARNING CLASSIFICATION | SCIKIT LEARN

This is a personal project i did which entails the classification of heart Disease (if a patient has heart disease or not). The project involves binary classification (a sample can only be one of two things). Which involves using a number of different features (pieces of information) about a person to predict whether they have heart disease or not. The data was gotten from CLEVELAND DATABASE.

Predicting Hospital Inpatient length of Stay

MACHINE LEARNING REGRESSION | SCIKIT LEARN

Using Machine Learning to Predict Hospital Length of stay(admission days) for Patients with SCHIZOPHRENIA and other PSYCHOTIC DISORDERS. The ability to predict how long a patient will stay, only with information available as soon as they enter the hospital and are diagnosed, can therefore have many positive effects for a hospital and its efficiency. A model that can predict patient length of stay could allow hospitals to better analyze the factors that influence length of stay the most. My article on medium . The data was gotten from NY Hospital Inpatient Discharges dataset.

ZuChat App

BACKEND DEVELOPMENT | DJANGO

Zuchat is a real-time chat App built with Python and Django. You can chat with anybody in a room (like group) that is connected in the same chat room. Multiple rooms can also be created. Link to App

EDA on Reviews Text Data

EXPLORATORY DATA ANALYSIS | NATURAL LANGUAGE PROCESSING

This project entails the exploratory data analysis and natural language processing (NLP) i carried out on women's e-commerce clothing reviews(text). Libraries used includes Numpy, Pandas, Matplotlib, Plotly and Seaborn. The data was gotten from KAGGLE.

NLP Question-Answering Model

NATURAL LANGUAGE PROCESSING | DEEP LEARNING

This is a personal project i did which entails extracting Text data from wikipedia about the past 46 Presidents of United States of America and then building an NLP question-Answering Model using the hugging-face API.

Blue Book for Bulldozers

MACHINE LEARNING REGRESSION | SCIKIT LEARN

This project entails predicting future auction sale price for a piece of heavy equipment to create a "blue book" for bulldozers. The data and evaluation metrics used is root mean squared log error (RMSLE), which was the instructions given on kaggle. The data was gotten from KAGGLE.

E-Commerce Site

BACK-END DEVELOPMENT USING DJANGO

This is a personal project i created with django. I developed the backend using django.

Predictive Modelling on Nigerian Bank Campaign Subscriptions

MACHINE LEARNING CLASSIFICATION | SCIKIT LEARN

I found patterns and built a predictive model on this dataset with the aim of forecasting the percentage of potential customers for the financial products of the bank. The evaluation metric used was 'Mean F1-Score'. The data was gotten from KAGGLE.

EDA on Boston Housing Dataset

EXPLORATORY DATA ANALYSIS

This project entails the exploratory data analysis i carried out on the boston housing dataset. Libraries used includes Numpy, Pandas, Matplotlib and Seaborn.

EDA on FIFA World Cup Matches

EXPLORATORY DATA ANALYSIS

This project entails the exploratory data analysis i carried out on FIFA World Cup Matches. Libraries used includes Numpy, Pandas, Matplotlib, Plotly and Seaborn. The data was gotten from KAGGLE.

EDA on The Titanic Dataset

EXPLORATORY DATA ANALYSIS

This project entails the exploratory data analysis i carried out on the titanic dataset. Libraries used includes Numpy, Pandas, Matplotlib, Plotly and Seaborn. The data was gotten from KAGGLE.

Great Motors Car Price Prediction

MACHINE LEARNING REGRESSION | SCIKIT LEARN

A Nigerian automobile company, Great Motors. The objective of the challenge is to predict the price (Amount (Million Naira)) the company should sell a car based on the available data (Location, Maker, Model, Year, Color, Amount (Million Naira), Type, Distance). The objective is to predict the selling price.