✨[FEATURE] Spam mail detector

[Niraj1608]

Email Spam Detector is a machine learning model that predicts whether an email is spam or not. It utilizes Multinomial Naive Bayes algorithm and LogicalRegression , NLTK, Matplotlib, and both CountVectorizer and TfidfVectorizer for feature extraction .

Description

The Email Spam Classifier is designed to analyze the content of an email and determine whether it is likely to be a spam or legitimate email. It uses a machine learning approach to classify emails based on their textual features.

The project includes the following components:

Multinomial Naive Bayes: The model is trained using Multinomial Naive Bayes, a popular algorithm for text classification, to learn the patterns and characteristics of spam and non-spam emails.

NLTK: The Natural Language Toolkit (NLTK) is a Python library that provides various tools and resources for natural language processing. It is used for preprocessing the email text and extracting relevant features.

Matplotlib: Matplotlib is a plotting library in Python. It is used for visualizing the performance metrics and results of the classifier, such as accuracy, precision, and recall.

Feature Extraction with CountVectorizer and TfidfVectorizer: The project utilizes both CountVectorizer and TfidfVectorizer for feature extraction. CountVectorizer converts the text data into numerical features by counting the occurrences of words, while TfidfVectorizer converts the text data into numerical features based on term frequency-inverse document frequency.

Deployment and gui : with straeamlit

[Niraj1608]

@suryanshsk assign me this issue :)