Welcome to my Apps repository. This repository contains different machine learning applications that I have built and deployed. Each application has its own directory with its code, documentation, and deployment information.
This text generation app deployed on Hugging Face using FastAPI can be used to generate text content based on a specific input or prompt. The app uses a pre-trained language model, such as GPT-2 or GPT-3, to generate text that is similar in style and tone to the input.
Users can interact with the app using this link . Click on "Try it Out" .The app generates the text and displays new content based on the input text back to the user.
One potential use case for this app is for content creation, where a user might use the app to generate ideas for articles, social media posts, or other types of written content.
This application is an Uplift Model. Uplift modeling is used to identify the customers who are most likely to be influenced by the effect of an advertising campaign and to quantify the size of that impact. It has been deployed to Streamlit platform and can be accessed at Uplift Demo App
This app shows a data analyis of the Supermarket Sales Dataset.
Objective The objective of this project is to perform an exploratory data analysis on the dataset and build machine learning models to predict the total sales and customer ratings. Link to Supermarket App
Each application has its own requirements, which can be found in their respective directories. In general, the following requirements are needed:
Python 3.8 Required Python packages, as listed in the requirements.txt file in each application directory Any additional dependencies specific to the application.
To run any of the applications in this repository, please follow these general steps:
Clone the repository to your local machine: git clone https://github.com/mazon1/Apps.git Navigate to the directory of the application you want to run: cd application1 Install the required packages: pip install -r requirements.txt Follow the specific instructions in the application's README.md file to run and use the application.
Feel free to contribute to this repository by creating a pull request or opening an issue. If you have any questions or feedback, please contact me on LinkedIn at-Uchenna Mgbaja
This repository is licensed under the MIT License. See the LICENSE file for more details.