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Welcome to the "Compozent_ML_AI_OCT23" repository, a compilation of machine learning and artificial intelligence projects focusing on solving real-world challenges. Authored by Viraj N. Bhutada, these projects demonstrate proficiency in advanced machine learning techniques.
Linear classifier using Support Vector Machines (SVM) which can determine whether an email is Spam or not with an accuracy of 98.7%. Used regularization to prevent over-fitting of data. Pre-processed the E-mails using Porter Stemmer algorithm. Used a spam vocabulary to create a Feature Vector for each E-mail. Prints the top 15 predictors of spam
Proyek ini bertujuan untuk memeriksa bahwa email yang diterima adalah spam atau ham melalui klasifikasi teks di WEKA menggunakan algoritma J48 Decision Tree dan Naive Bayes Multinomial Text.
This is an Email/SMS spam detection system, built as a project for AutumnnHacks Hackathon. It classifies messages you recieve on emails and sms as spam or not spam.
One of the primary methods for spam mail detection is email filtering. It involves categorize incoming emails into spam and non-spam. Machine learning algorithms can be trained to filter out spam mails based on their content and metadata.