Building a Spam Filter with Naive Bayes

In this project, you'll take on the role of a data scientist tasked with building an SMS spam filter using the multinomial Naive Bayes algorithm. You'll work with a real-world dataset to clean and prepare text data, calculate probabilities, and train the algorithm to classify messages as spam or ham. This hands-on project allows you to apply your knowledge of conditional probability and Naive Bayes to solve a practical problem. You'll strengthen your skills in data preparation, probability calculations, and implementing machine learning algorithms in Python. The project will be a valuable addition to your portfolio, demonstrating your ability to build a functional spam filter. **Objective:** Use the multinomial Naive Bayes algorithm to create an SMS spam filter in Python, developing your machine learning skills with a practical application.