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Kursus Identifying Spam Emails - Online-undervisning med certifikat
python

Identifying Spam Emails

Kyryl Sidak

Python

11 Chapters

0 Studying now

We are going to classify emails as spam or non-spam by analyzing the content of the emails. We will preprocess the text data using techniques like tokenization and vectorization, then apply machine learning to build and evaluate a classification model, namely Logistic Regression. By the end of the project, we aim to develop a reliable tool for identifying spam emails.

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Teknologi

Python

Sprog

En

Bedømmelse

Kapitler

11

Loading the Dataset

Columns Adjustments

Preliminary Analysis

Plotting the Target Distribution

Text Cleaning

Tokenization

Features and Target Variable

Train-Test Split

Vectorization

Modeling

Evaluating the Model

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Loading the Dataset

Columns Adjustments

Preliminary Analysis

Plotting the Target Distribution

Text Cleaning

Tokenization

Features and Target Variable

Train-Test Split

Vectorization

Modeling

Evaluating the Model

Beskrivelse af kurset

We are going to classify emails as spam or non-spam by analyzing the content of the emails. We will preprocess the text data using techniques like tokenization and vectorization, then apply machine learning to build and evaluate a classification model, namely Logistic Regression. By the end of the project, we aim to develop a reliable tool for identifying spam emails.

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