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30-days-of-learning

The 30 days of learning program was powered by Microsoft, the programme was designed to help upskill with Microsoft technologies by learning and building solutions across these knowledge areas; Data Analysis Using Power BI, Low-code/No-Code Application Development using Power Platform, and Data Science and Machine Learning with Azure. This repo contains my notes from the program. The main page is accessible via https://aka.ms/30DLOnboardingRecap

agrobot

Agrobot is the modern farmer's A.I assistant, Agrobot is built to help farmers detect crop diseases or pests on the farm through snapshots. It is basically a host to Computer vision models built for farm use. Agrobot gives brief explanations on the detected subject, as well as proffer the latest solutions. Agrobot also supports over 150 languages.

agrobot-apis

This repository contains a set of APIs built for Agricultural based use cases

agrobotfarms

https://agrobotfarms.netlify.app/

ai-business-school-classification-task

The notebook shows how to perform Exploratory Data Analysis, Predictions and Model Selection on a multi-class dataset.

aicoding

Empower developers with a human-AI collaborative VSCode extension

airqo-frontend

This repository contains the frontend applications for the AirQo platform.

android-demo-app

PyTorch android examples of usage in applications

awesome-datascience

:memo: An awesome Data Science repository to learn and apply for real world problems.

busara-mental-health-prediction-challenge-indabax-nigeria

Building a model which accurately predicts which individuals are likely to be depressed from the survey data could be used by mental health providers such as local clinics, NGOs or community health volunteers to reach out to those at risk.

cgiar_wheat_growth_stage_challenge

Rank 5/204

chemotron-x

The machine learning algorithm predicts the value of carbon at any time in the past, present or future and in any location.

chemotronix

A Machine Learning model that predicts CO2 emissions values for a specified place and time

climdes

darknet

YOLOv4 (v3/v2) - Windows and Linux version of Darknet Neural Networks for object detection (Tensor Cores are used)

datafest-africa-noise-pollution-classification-challenge

Due to the widespread noise pollution in our cities, data sponsors Sunbird AI recognised a need to gather data on noise exposure, in order to produce an action plan and empower citizens to be vigilant in tracking and monitoring noise. The challenge is to train a noise classification model to classify noise into different categories.

deploy_insurance_pred2

deploy_insurance_pred2

deploying-machine-learning-models

Example Repo for the Udemy Course "Deployment of Machine Learning Models"

derotate

Deep learning web app that understands if/how an image is rotated and "derotates" it

descision-trees-and-visualization

The notebook was created in fulfillment of my internship at The Sparks Foundation, the notebook explains clearly how to use decision trees to train data, build model, predict with the model as well as evaluate the model. The final section of the notebook visualizes the decision tree itself, with a clear understanding of how the model makes predictions.

diffusion-nbs

Getting started with diffusion

dotnetconf-studentzone

.NET Student Zone .NET Conference 2022

dsn-2023-bootcamp-qualification

exploration-of-transfer-calibration-for-iot-enabled-cems

This repository features an IoT-Based Emissions Monitoring System, aiming to create a low-cost, real-time solution using IoT, machine learning, and decentralized data storage. It includes sensor calibration, CO2 emission prediction, and calibration transfer. Stay tuned for updates.

exploratory-data-analysis-retail

farmx

This repository contains Team FarmX's solution for the Google Solution Challenge 2023.

farmx-mobile

flask-api

:globe_with_meridians: A simple REST API project developed with Python Flask

free-ai-classes-in-every-city-hackathon

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, Colour, Amount (Million Naira), Type, Distance). The objective is the predict the selling price. About Data Science Network (datasciencenigeria.org)

gbv-hackathon

This contains my solution for the Gender-Based Violence Tweet Classification Challenge hosted on Zindi