Spam email detection

Email Spam Classification/readme.md

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+# Spam Email Classification https://github.com/World-of-ML/DL-Simplified/issues/340
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+Full name : Aindree Chatterjee
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+GitHub Profile Link : https://github.com/aindree-2005
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+Email ID : [email protected]
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+Program : CodePeak
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+Approach for this Project :
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+**LSTM**
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+Long Short-Term Memory (LSTM) is a type of recurrent neural network (RNN) designed for processing and predicting sequences. To detect spam, LSTM can analyze patterns in email or text sequences, identifying suspicious content based on contextual relationships and learning from sequential data to make accurate predictions about the likelihood of spam.
+**BERT**
+BERT (Bidirectional Encoder Representations from Transformers) is a pre-trained natural language processing model. To detect spam, fine-tune BERT on labeled spam/ham data. Use the trained model to predict whether new messages are spam based on their language context, achieving more accurate spam detection compared to traditional methods.
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