sekinat-oyero Goto Github PK

2016-ml-contest

Machine learning contest - October 2016 TLE

alx-low_level_programming

alx-system_engineering-devops

alx-zero_day

I'm now a ALX Student, this is my first repository as a full-stack engineer

awesome-machine-learning

A curated list of awesome Machine Learning frameworks, libraries and software.

background-generator

cyclistic-case-study

In this project, I analysed over 5 million of Cyclistic bikeshare data spanning 12 months using SQL and Python

dezoomcamp24

ds-ml-initiative

earthquake-data-analysis

In this project, I analyzed and visualised over 200 thousand household surveys of the 7.8Mw earthquake that happened in Gorkha region in April, 2015.

end-to-end-ml

first-contributions

🚀✨ Help beginners to contribute to open source projects

geo-python-week-2021

hamoyeint

heathcare-data-analysis

In this project, I used Python and its libraries to wrangled and analyzed more than 100k Medical Appointments data in Brazil to derive insights on the reasons why patients missed or showed up for their appointments.

machine-learning-tutorials

machine learning and deep learning tutorials, articles and other resources

marketing-database-design

In this project, I cleaned a bank personal loan marketing campaign dataset, and designing the schema in a way that would allow data from future campaigns to be easily imported in PostgreSQL database.

mindsdb

MindsDB is a Server for Artificial Intelligence Logic. Enabling developers to ship AI powered projects to production in a fast and scalable way.

ml-foundations

Machine Learning Foundations: Linear Algebra, Calculus, Statistics & Computer Science

principles-of-machine-learning-python

Principles of Machine Learning Python

sekinat-oyero

About

sekinat-oyero.github.io

Website

supervised-machine-learning

In this project, I developed a Random Forest Classifier model to predict fake bank notes using Python

teensinai

twitter-data-analysis

In this project, I queried dataset from Twitter using Twitter API and carried out data quality assessment, cleaning, and visualisation and created a descriptive report on the analysis and findings.