Joana Owusu-Appiah's Projects
Generate random identities for people in a phone book
this simple app is able to calculate BMI given a person's weight (kg) and height(cm)
the ML model predicts the prices of houses in Boston
a repository made up of capstone project. The project has advanced image analysis concepts, classical machine learning and deep learning applied to Brain tumor MRI images
[STILL ACTIVE] Learn the GitHub workflow by contributing code in a fun simulation project
SQL project. Data is forked from (https://gist.github.com/pamelafox/ad4f6abbaac0a48aa781) and has been updated with my analysis.
This notebook is a crash course on data visualisation with matplotlib and seaborn.
Azubi database challenge
Early stage diabetes risk prediction datasets
an innovative web-app that provides access to mental health professionals and resources.
adapted from sololearn platform to give leaners an introduction to data science concepts data manipulation, analysis, visualisation, linear regression, logistic regression
The folder contains an excel dashboard, a power bi report and a word document report.
SQL project: the task was to create data of famous artists and describe what they do. Query the data created with SQL statements.
Image segmentation using colour spaces in openCV + python
With this repo I try my hands on flask blueprint architecture.
used to practice git hub commands
Group members learning and familiarizing with basic git concepts
This is a python file to guess numbers
A project that extracts features and makes classifications based on the weather dataset.
Up-to-date version of labs for ISLP
30 Day Vanilla JS Challenge
My personal repository to share with the world my interests and cool projects I would be working on.
using machine and deep learning techniques to segment and classify brain tumors on T1 weighted MRI images
a neural network is built using pytorch on the MNIST database
First assignment for Applied python class. The assignment required that we simulate the switch door strategy of the Monty hall game in python
Attempting to reach a 96% accuracy on the MNIST dataset with MLP using basic techniques (increasing hidden layers and increasing neurons)