03.10.2024
Yeah i like the tutor aaand it's short
Master machine learning with Naïve Bayes: learn the theoretical foundations behind the Bayesian approach and gain practical problem-solving skills
$99.00
$79.00
What you get:
$99.00
$79.00
What you get:
$99.00
$79.00
What you get:
Industry leaders and professionals globally rely on this top-rated course to enhance their skills.
Knowledge on various machine learning algorithms is essential for machine learning enthusiasts and specialists. This course focuses on a specific type of classifier – the Naïve Bayes one. It is famous for being a quick learner and a real-time problem solver. Not only will you learn the theoretical foundations behind the Bayesian approach, but you will also get the chance to solve a real-life problem using scikit-learn’s Naïve Bayes algorithms.
1.1 What does the course cover?
1.2 Motivation
1.3 Bayes' thought experiment
1.0 Assignment 1
1.4 Bayes' theorem
1.5 The ham-or-spam example
Practice what you've learned with coding tasks, flashcards, fill in the blanks, multiple choice, and other fun exercises.
This section serves as a theoretical introduction to the Bayesian approach which will later help us understand the Naïve Bayes machine learning classification algorithm. We start with an intuitive example which Thomas Bayes himself introduced. Then, we dive into the mathematics behind his approach and derive Bayes’ theorem. Finally, we apply this theorem to classify an e-mail message as a spam or not-spam (also known as a ham).
In this section you will learn how to install all Python packages relevant for the next part of the course focused on practice.
This is the practical section of the course where we roll our sleeves up and build our very own classification model. We use a dataset containing YouTube comments – some well-intended and others harmful. Our task is to train a model that could later serve as a spam comment detector. To do this, we make use of Python’s scikit-learn library, where a Naïve Bayes algorithm is implemented. Throughout this section, we will study the inner workings of the algorithm and learn how to interpret performance metrics such as accuracy, precision, recall, and F1 score.
Level of difficulty: Intermediate
A 365 Data Science Course Certificate is an excellent addition to your LinkedIn profile—demonstrating your expertise and willingness to go the extra mile to accomplish your goals.
Hristina Hristova is a Theoretical Physicist with experience in the fields of mathematics, physics, programming, and the creation of various educational content. For several years now, she has been tutoring physics and mathematics students online, following educational programs such as The IB Diploma, Cambridge IGCSE, and Cambridge AS & A Level, among many others. Hristina’s high qualification and adaptive teaching style have helped plenty of students successfully pass their exams, while also enjoying the learning process.
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