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Which of the following contains the most number of HTML emails?
Spam
Ham
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1 Spam Classifier - Step 1- Get the SpamAssassin Dataset from their Website
2 Spam Classifier - About the Spam Dataset
3 Spam Classifier - Fetch the Dataset
4 Spam Classifier - Call the Function
5 Spam Classifier - Load all Emails
6 Spam Classifier - Step 2 - Parse the Emails
7 Spam Classifier - Parse the Emails
8 Spam Classifier - Step 3 - Explore the Emails
9 Spam Classifier - Check Content of Emails
10 Spam Classifier - Looking at Type of Email Structures
11 Spam Classifier - Most plain text emails
12 Spam Classifier - Most HTML emails
13 Spam Classifier - Step 4 - Preprocess the Data
14 Spam Classifier - Split the Dataset
15 Spam Classifier - Create a Preprocessing Function
16 Spam Classifier - Test HTML to Plain Text Function
17 Spam Classifier - Step 5 - Create Word Counts from Emails
18 Spam Classifier - Create Transformer to Convert Emails to Word Counters
19 Spam Classifier - Try the Transformer on few Emails
20 Spam Classifier - Step 6 - Convert Word Counts to Vectors
21 Spam Classifier - Create Transformer to Convert Word Counts to Vectors
22 Spam Classifier - Step 7 - Create Processing Pipeline
23 Spam Classifier - Create a Pipeline to Transform the Entire Dataset
24 Spam Classifier - Step 8 - Create Logistic Regression Model
25 Spam Classifier - Train a LogisticRegression model on the Dataset
26 Spam Classifier - Step 9 - Evaluate the Model
27 Spam Classifier - Calculate the Precision and Recall for the model
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