ML-Sentiment

Create to Deploy ML Sentiment Models Using Flask.

This guide provides step-by-step instructions on how to run this models in your own local environment.

Prerequisites

Make sure you have the following installed:

• Python (version 3.10.12)
• Pip (Python package installer)
• Anaconda or Miniconda (for managing Python environments) : Anaconda Docs

Step 1: Clone the Repository

Clone this repository to your local machine using the following command:

git clone <repository_url>

Step 2: Create and Active conda virtual env

cd your_project_directory
conda create --name my_env python=3.10.12

• On Windows :

conda activate my_env

• On MacOs or Linux :

source activate my_env

Step 3: Install Required Dependencies

pip install -r requirements.txt

Step 4: Starting a Flask API with a Trained Model

python app.py

Step 5: Access the Model/Application

For web-based applications or APIs, access them through the specified endpoints or URLs. For example: http://localhost:5000