April 2021
Intermediate to advanced
11h 10m
English
Overview
In this 11-hour course, you'll explore the world of Machine Learning with a focus on the Support Vector Machine (SVM) algorithm, using Python programming. You'll learn through step-by-step instruction, covering both theoretical and practical aspects with hands-on experience.
What I will be able to do after this course
- Understand the core concepts of Machine Learning and differentiative models.
- Acquire practical Python skills for implementing Machine Learning algorithms.
- Learn the mathematical foundations and workings of Support Vector Machines.
- Develop the ability to preprocess data for machine learning tasks.
- Gain experience in applying SVM using real-world datasets in Python.
Course Instructor(s)
AI Sciences has extensive experience teaching courses in data science, machine learning, and programming. Their practical approach ensures that learners not only understand theoretical concepts but also gain real-world application skills. Their students appreciate the clarity and structured delivery in their lessons.
Who is it for?
This course is aimed at beginners who are eager to explore Machine Learning and Python programming. It is suitable for individuals with little to no prior experience in the field. Learners interested in understanding the mathematical principles of SVM or looking to strengthen their data analysis skills will find this course invaluable. By the end, students will be equipped to apply SVM techniques to datasets and progress further in their machine learning journey.
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