Build a Spam Detector AI with Text Classification
Course
Online
Description
-
Type
Course
-
Methodology
Online
-
Start date
Different dates available
In this course we’ll use Python 3 to create an Artificial Intelligence (AI) that can determine when an incoming email is spam or not. The technique we’ll use to create this cool project is called Text Classification. The group of algorithms that we’ll cover and use is Naive Bayes. Using term frequency and inverse document frequency we’ll be able to tweak our AI for improved accuracy.
To build our AI we’ll use the publicly available Enron dataset.
Frameworks and tools covered: Python 2.7 (updated for Python 3.6), Anaconda 5.2, Enron Dataset, NumPy 1.13, SciPy 0.19
Your Courses, Your Way
All of our project-based courses are designed to be flexible – you can access courses 24/7 to fit them around your schedule, and choose the learning materials that suit you best.
You can even download your course videos and watch them offline using the Zenva app, available on iOS and Android.
Learn from World-Class Instructors
Our course instructors participate in elite developer programs and have been recognized for their demonstrated excellence in development and teaching.
That way, you can be confident that you’re learning the most up-to-date content from industry experts.
Interactive Lessons with Codemurai
Our unlimited access package comes with free access to all of the courses in our mobile app, Codemurai!
Available on iOS and Android, it’s full of interactive programming lessons and exercises so you can continue your learning on the go.
Achieve Real Results
Our community of 1,000,000+ learners and developers have used the skills learned with us to publish their own games and websites, land their dream jobs, and even start their own businesses – and you have the potential to do the same!
Check out what our learners think below:
I love the lectures, concise course objectives, and how they not only teach you enough to get started, but prepare you for the advanced stuff later down the road.
⭐⭐⭐⭐⭐
– Mihir Patel
Facilities
Location
Start date
Start date
About this course
b
Why should I learn programming?
b
What will I achieve by taking these courses?
b
Technology changes quickly. What happens if the content becomes outdated?
b
I’m an absolute beginner who’s never coded before. Can I still do these courses?
b
What time commitment is needed?
b
Will these courses help me to change my career?
b
Can I watch the videos offline?
Intermediate knowledge of Python 3
Intermediate knowledge of using NumPy
Intermediate knowledge of machine learning
Reviews
This centre's achievements
All courses are up to date
The average rating is higher than 3.7
More than 50 reviews in the last 12 months
This centre has featured on Emagister for 4 years
Subjects
- Access
- Project
Course programme
Introduction 2:49
Introduction 2:49
2:49
Development Environment - Anaconda 8:04
Development Environment - Anaconda 8:04
8:04
M1-1 Text Classification 10:03
M1-1 Text Classification 10:03
10:03
M1-2 Naive Bayes 1 10:18
M1-2 Naive Bayes 1 10:18
10:18
M1-3 Naive Bayes 2 10:59
M1-3 Naive Bayes 2 10:59
10:59
M1-4 Naive Bayes 3 12:18
M1-4 Naive Bayes 3 12:18
12:18
M1-5 Numerical Representations of Text 10:53
M1-5 Numerical Representations of Text 10:53
10:53
M1-6 tf-idf 10:34
M1-6 tf-idf 10:34
10:34
M2-0 Downloading the Dataset
M2-0 Downloading the Dataset
M2-1 Intro to Enron Dataset 9:35
M2-1 Intro to Enron Dataset 9:35
9:35
M2-2 Intro to Provided Code 9:31
M2-2 Intro to Provided Code 9:31
9:31
M2-3 Count Vectorizer 10:00
M2-3 Count Vectorizer 10:00
10:00
M2-4 tf-idf 9:29
M2-4 tf-idf 9:29
9:29
M2-5 Naive Bayes Classifier 12:43
M2-5 Naive Bayes Classifier 12:43
12:43
M2-6 Pipelining 11:40
M2-6 Pipelining 11:40
11:40
Conclusion 2:21
Conclusion 2:21
2:21
Additional information
Build a Spam Detector AI with Text Classification
