Creating and Deploying a Machine Learning Model: From Jupyter Notebooks to AWS EC2 & Web Application

In this video, I walk you through the entire process of creating, deploying, and hosting a machine learning model. Whether you're a data science enthusiast, an aspiring machine learning engineer, or a professional looking to enhance your deployment skills, this tutorial provides a comprehensive guide.

What's Covered in This Video:

Building the Machine Learning Model:

Explore the steps of building a predictive model using Python in Jupyter Notebooks.
Understand the data preprocessing, model training, and evaluation processes.
Get insights into how to select and fine-tune the best machine learning model for predicting outcomes.
Deploying the Model on AWS EC2:

Learn how to set up an Amazon EC2 instance for deploying your machine learning model.
Step-by-step instructions for securely transferring files and configuring your instance.
Running a Flask application on the EC2 instance using gunicorn for production-grade deployment.
Creating a User-Friendly Web Application:

Discover how to design and develop a web interface that allows users to interact with your model.
Implementing HTML, CSS, and Flask to create a responsive and informative webpage.
Real-time prediction and probability calculation display through the web app.
Connecting Everything Together:

Integrate the model with the web application to enable real-time predictions.
Ensure the application is accessible from the internet with the appropriate security measures in place.
Who Should Watch This Video:

Data Scientists and Machine Learning Engineers looking to deploy models in a real-world scenario.
Web Developers interested in integrating machine learning models into web applications.
IT professionals seeking to learn more about AWS services and secure deployment practices.
Tools and Technologies Used:

Python: Programming language for model development.
Jupyter Notebooks: Environment for data analysis and model building.
Flask: Web framework for building the web application.
AWS EC2: Cloud service for deploying and hosting the application.
Gunicorn: WSGI server to run the Flask app in production.
Whether you're deploying a machine learning model for the first time or looking to refine your skills, this video provides valuable insights and practical steps to take your project from concept to deployment.

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