About This Class
This class has the purpose to make you understand the theory behind the popular Naïve Bayes Classifier method used in Machine Learning and to teach you how to implement it in code, using Python.
Therefore, the course is divided into 2 parts: a theoretical one and a practical one.
We are also going to implement other popular Machine Learning algorithms and compare the performances with our proposed Naïve Bayes technique.
What are the requirements?
Basic knowledge of Python programming is preferred but not required.
What am I going to get from this course?
Learn a new method used frequently in Machine Learning.
Learn how to implement it in code.
Learn how to implement other popular Machine Learning models in code and how to compare the performances with a concrete example.
Who is the target audience?
Anyone interested in Data Science.
Anyone interested in implementing Machine Learning models with Python.
Anyone interested in Statistics.
Anyone considering AI or Data Science as a future career path.
Current Data Science or AI students that want to improve their knowledge.