gkokonya Goto Github PK

bloglaravelui

This is a user interface for a laravel blog

captain-gbk

Mpesa

computer-networking-projects

data-science-machine-learning-loan-prediction

Company wants to automate the loan eligibility process (real time) based on customer detail provided while filling online application form. These details are Gender, Marital Status, Education, Number of Dependents, Income, Loan Amount, Credit History and others. To automate this process, they have provided a dataset to identify the customers segments that are eligible for loan amount so that they can specifically target these customers.

data-science-machine-learning-zinmat-insurance-recommendation

Zinmat Insuarance Recommendation Engine is trying to predict which insurance product an existing customer will want next

data-warehousing-crime-data-mart

;This a Data Warehouse project done using Microsoft SQL Server Intergration Services. This was done by

laravel-crud

A web Application that stores car details

laravel-mpesa-stk

luggage-management-system

microsoft-access-database-project

Kabumbu Football League Information System

mpesa-api

natural-language-processing-multiclass-text-classifiation

Around 1 in 4 people will experience a mental health problem this year. Low-income countries have an estimated treatment gap of 85% (as compared with high-income countries with a gap of 35% to 50%). While Kenya has a mental illness prevalence rate that is comparable to that of high-income countries, there are still less than 500 healthcare professionals serving the country. In Kenya, there are growing concerns about mental health among young people, particularly university students that face a challenging and unique conflation of stressors that put them at risk of challenges like depression and substance abuse. From the use of app-based solutions for screening to electronically delivered therapies, the use of technologies including machine learning and AI will potentially transform the delivery of mental health services in the coming years. The objective of this challenge is to develop a machine learning model that classifies statements and questions expressed by university students in Kenya when speaking about the mental health challenges they struggle with. The four categories are depression, suicide, alchoholism, and drug abuse. This solution will be used for a prototype of a mental health chatbot designed specifically for university students. This initiative is a first step in leveraging technology to make mental health services more accessible and more user-friendly for young people in Kenya and around the world.

project-search

Laravel based project

simple-blog

Blog website with Laravel 9

simple-etl-process

Using Student source file ,performing ETL-Process and Visualizing data using Power BI

student-attendance-management-system-using-barcode-identification-

test

vuejs-laravel-blog