Build Your First Email Spam Classifier – A Practical ML

Build Your First Email Spam Classifier – A Practical ML is a beginner-friendly international workshop that offers a perfect gateway into the world of machine learning. Through the creation of an end-to-end spam detection system, participants will learn essential ML concepts including data preprocessing, feature extraction, model training, evaluation, and performance tuning. With a strong emphasis on hands-on coding and practical implementation, learners will walk away with both knowledge and a portfolio-ready project.

To introduce participants to machine learning (ML) through a practical, real-world application: building an email spam classifier using Python. The workshop aims to cover the complete ML pipeline from data preparation to model deployment in an easy-to-understand, hands-on format.

Day 1: Understanding the Problem and Preparing Your Data ● ML Basics & Spam Filtering Relevance ● Setting Up Google Colab ● Exploring & Cleaning Spam Dataset Day 2: Building and Training the Decision Tree Model ● Feature Engineering ● Training a Decision Tree Classifier ● Intro to Model Evaluation Day 3: Evaluating, Optimizing & Deploying Your Model ● Confusion Matrix & Hyperparameter Tuning ● Visualizing Decision Tree ● Real-world Use & Deployment Ideas