VictorOwinoKe

Victor Owino's repositories

CNN-Image-classification-Using-Fashion-MNIST-dataset

There's been much speculation in recent years about neural networks technologies and other deep learning algorithms, primarily because of the popularity of several implementations in the sector utilizing these techniques. Consequently, this hype has yielded several innovative ideas to build open-source libraries and methods to enable the average income tech-savvies to achieve their objective. This research paper aims to examine and illustrate how to use deep learning technologies and algorithms to precisely classify a dataset of fashion images into their respective clothing categories. First, the paper shows the general knowledge of convolutional neural networks (CNN) and the techniques of image classification. Later on, it also discusses the methodology of building a neural network and the simulation process. The results of the neural network simulation are compressively evaluated and discussed.

Language:Jupyter NotebookMIT4 10

Health_Access_Flask

The app has 2 portals, one for the patients requiring the appointment, and the doctors available for consultation. The patients can enter their medical history, any undergoing medication, etc which can be viewed by the doctor if he/she confirms their appointment. The index page of the patient and the doctor shows all their upcoming consultations. The doctor is notified if there are any patients requiring their appointment, and have the option to either confirm or deny, which causes a corresponding notification to be sent to the patient. The doctor can also send the prescription with detailed feedback to the patient after consultation, along with the consultation fee to be paid. The patient can view the feedback in the history tab of their portal, which also provides the facility to pay the consultation fee by redirecting them to the Google Pay web page.

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LaBELLE-store-Django-Ecommerce

La BELLE Fashion Store is an online Fashion store duild using python Django

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After-Work-Data-Science-Project-ShowCase-EDA

You work for Lublu as a Data Science Consultant and you have been tasked to perform analysis on pricing, product and assortment of Adidas and Nike. Create a descriptive analysis report, making relevant observations and recommendations that will help Lublu in the launch of such similar products.

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Binary-Heap-Tree-Python-implementation

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Data-Analysis-Python-Projects

Learning Python is crucial for anyone interested in working with data. This repository showcases my Python projects, demonstrating my ability to analyze, manipulate and automate data analysis using python

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Data-Vizualization-and-Dashboards-Power-BI-

This repository showcases my sample projects through live data dashboards, interactive reports, charts, graphs, and other visual representations, that demostrate how we can use data visualization to helps users develop powerful business insight quickly and effectively.

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EDA-on-IT-Salary-Suevey-2020

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Machine-Learning-from-Disaster-Titanic-Dataset

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python-turtlelab-Snake-game

Wow, was having some turtle lab excercises then i thought of building a snake game..

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Simple-Hospital-Management-Sytem

Hospital Management system is open source Application use to mange the the whole activity of Hospital like Patient , Doctor,Appointment . It is developed in Python Flask and Database text files.

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SQL-Porfolio-Projects-DDL-DML

SQL is a must-have skill for any aspiring data practitioner. Many modern companies store vast amounts of their data in various tables of relational databases. To extract the necessary data from a database for further manipulation and data analysis, you must have a good grasp of SQL. This repository serves as a showcase for my SQL projects

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UoM-DESIGN-THINKING-

Design thinking ; python foundamentals

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-La-BELLE--heroku-app

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AI-in-Niomedicine-and-Epidermology

AI is transforming the practice of medicine.

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Assignment-Single-sever-Queueing-Simulation

The single-server queuing model that will be simulated is as follows. (1).The simulation will end when n = 1000 delays in queue have been completed. (2). The interarrival and service times will now be modeled as independent random variables from exponential distributions with mean 1 minute for the interarrival times and mean 0.5 minute for the service times.

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