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Ibrahim Odumas Odufowora's Projects

linearsvm icon linearsvm

This project involves the implementation of efficient and effective LinearSVC on MNIST data set. The MNIST data comprises of digital images of several digits ranging from 0 to 9. Each image is 28 x 28 pixels. Thus, the data set has 10 levels of classes.

logistic_regression icon logistic_regression

This project involves the implementation of efficient and effective Logistic Regression (FROM SCRATCH) classifiers on MNIST data set. The MNIST data comprises of digital images of several digits ranging from 0 to 9. Each image is 28 x 28 pixels. Thus, the data set has 10 levels of classes.

machinealgorithm icon machinealgorithm

I developed a function to perform regularized linear and Gaussian basis functions for regression. Some dataset from the UCI machine learning repository were used to validate the function.

multi_layer_perceptron icon multi_layer_perceptron

This project involves the implementation of efficient and effective MLP (multi-layer perceptron) on MNIST data set. The MNIST data comprises of digital images of several digits ranging from 0 to 9. Each image is 28 x 28 pixels. Thus, the data set has 10 levels of classes.

my_knn_pca_mnist icon my_knn_pca_mnist

Problems Identification: This project involves the implementation of efficient and effective KNN classifiers on MNIST data set. The MNIST data comprises of digital images of several digits ranging from 0 to 9. Each image is 28 x 28 pixels. Thus, the data set has 10 levels of classes.

naivebayes_mnist icon naivebayes_mnist

I implemented a Naive Bayes classifier form scratch and applied it on MNIST dataset.

restpy icon restpy

Implemented a production ready RESTful API with Connexion, OpenAPI, Flask, and Gunicorn libraries/technologies.

svm_polynomial_kernel icon svm_polynomial_kernel

This project involves the implementation of efficient and effective polynomial SVC on MNIST data set. The MNIST data comprises of digital images of several digits ranging from 0 to 9. Each image is 28 x 28 pixels. Thus, the data set has 10 levels of classes.

svm_radial_kernel icon svm_radial_kernel

This project involves the implementation of efficient and effective RBF SVC on MNIST data set. The MNIST data comprises of digital images of several digits ranging from 0 to 9. Each image is 28 x 28 pixels. Thus, the data set has 10 levels of classes.

swapi icon swapi

Pulling and working with data from the Star Wars API.

swapi-scala icon swapi-scala

Pulling and working with data from the Star Wars API.

thyroid_disease icon thyroid_disease

The thyroid gland is an endocrine gland. The thyroid organ discharges thyroxine (T4) and triiodothyronine (T3) into the bloodstream as the principal hormones. The capacities of the thyroid hormones are to direct the rate of digestion system and affect the overall development of the human body.

travelapp_ios icon travelapp_ios

iOS application for real-time airport status and currency conversion.

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