Email Spam Detection (99% Accuracy) | Python Machine Learning Project 01 (Part 01)
Are you looking to build an email spam detection, SMS spam detection classifier, or a web app integrated with machine learning?
Welcome to my channel! In this video, we’ll walk through an exciting project: building an Email Spam Detection system with 99% accuracy. This project has two parts. In the first part, we’ll focus on developing and training the machine learning model using Google Colab. In the second part, we’ll integrate the model into a Django web application to create a user-friendly interface. This project is perfect for anyone interested in data science, AI, and machine learning, whether you’re a beginner or an experienced developer.
Dataset: https://drive.google.com/file/d/1MQQd...
Google Colab:
https://colab.research.google.com/
Time Stamps:
00:00 - Overview
00:50 - Code in Google Colab
03:50 - Libraries Imported
09:16 - Print Accuracy
13:29 - Give Input to Predict
14:26 - Next part Overview
What You'll Learn:
How to handle and preprocess text data using Pandas.
How to convert text data into numerical format using CountVectorizer.
How to split your dataset into training and testing sets for model evaluation.
How to train a Naive Bayes classifier for spam detection.
How to evaluate model performance using accuracy metrics.
How to create a prediction function to classify messages as spam or ham.
How to build a simple web interface using Django, so end users can easily use the spam detector without coding knowledge.
Channel Link:
/ @mr.data_scientist
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Github: https://github.com/MrAliHasan/
Instagram: / mr.data_scientist1
LinkedIn: / ali-hassan-rai
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