Diabetes Prediction Using Machine Learning With Python || Build AI Model with Deployment

🎯 Diabetes Prediction Using Machine Learning With Python | End-to-End Project with Deployment 🧠💻

Welcome to this hands-on tutorial where we build a Machine Learning model to predict diabetes using Python! In this video, you’ll learn everything from data preprocessing to model training and finally deploying the project using Streamlit.

📌 What You’ll Learn:
✅ How to load and clean the diabetes dataset
✅ Exploratory Data Analysis (EDA)
✅ Building a classification model using Logistic Regression
✅ Model evaluation and accuracy checking
✅ Saving the model using Pickle
✅ Creating a Streamlit web app for predictions
✅ Deploying your model online for real-time usage

🚀 Whether you’re a beginner in machine learning or looking to create your first deployed AI project, this video will guide you step-by-step.

📂 Dataset Link:

💡 Technologies Used:

Python

Pandas, NumPy, Scikit-learn

Streamlit

Pickle

Deployment platform (Render/Streamlit Cloud)

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