“The projects helped me apply what I learned and understand how to tackle all the little things that come along in real life.”

Data Analyst

## Project overview

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.

## Key skill required

### To complete this project, it's recommended to build these foundational skills in Python

• Assigning probabilities based on specific conditions
• Updating probabilities using prior knowledge
• Employing Naive Bayes for spam filter classification
• Applying the multinomial Naive Bayes algorithm

## Master skills faster with Dataquest

### Go from zero to job-ready

Learn exactly what you need to achieve your goal. Don’t waste time on unrelated lessons.

Build confidence with our in-depth projects, and show off your data skills.

### Challenge yourself with exercises

Work with real data from day one with interactive lessons and hands-on exercises.

Share the evidence of your hard work with your network and potential employers.

## The Dataquest guarantee

Dataquest has helped thousands of people start new careers in data. If you put in the work and follow our path, you’ll master data skills and grow your career.

We believe so strongly in our paths that we offer a full satisfaction guarantee. If you complete a career path on Dataquest and aren’t satisfied with your outcome, we’ll give you a refund.

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98%
of learners recommend
4.85
Dataquest rating
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\$30k
Average salary boost
for learners who complete a path

### Aaron Melton

“Dataquest starts at the most basic level, so a beginner can understand the concepts. I tried learning to code before, using Codecademy and Coursera. I struggled because I had no background in coding, and I was spending a lot of time Googling. Dataquest helped me actually learn.”

### Jessica Ko

#### Machine Learning Engineer at Twitter

“I liked the interactive environment on Dataquest. The material was clear and well organized. I spent more time practicing then watching videos and it made me want to keep learning.”

### Victoria E. Guzik

#### Associate Data Scientist at Callisto Media

“I really love learning on Dataquest. I looked into a couple of other options and I found that they were much too handhold-y and fill in the blank relative to Dataquest’s method. The projects on Dataquest were key to getting my job. I doubled my income!”

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