Math for Machine Learning

Math for Machine Learning

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What you will learn

Refresh your machine learning knowledge. Apply fundamental techniques of machine learning. Gain a firm foundation in machine learning for furthering your career. Learn a subject crucial for data science and artificial intelligence.

Curriculum

Section 1: Linear Regression

Section 2: Linear Discriminant Analysis

Section 3: Logistic Regression

Section 4: Artificial Neural Networks

Section 5: Maximal Margin Classifier

Section 6: Support Vector Classifier

Section 7: Support Vector Machine Classifier

Section 8: Penetration Testing by Kali Linux

Course Description

Would you like to learn a mathematics subject that is crucial for many high-demand lucrative career fields such as: Computer Science Data Science Artificial Intelligence If you're looking to gain a solid foundation in Machine Learning to further your career goals, in a way that allows you to study on your own schedule at a fraction of the cost it would take at a traditional university, this online course is for you. If you're a working professional needing a refresher on machine learning or a complete beginner who needs to learn Machine Learning for the first time, this online course is for you. Why you should take this online course: You need to refresh your knowledge of machine learning for your career to earn a higher salary. You need to learn machine learning because it is a required mathematical subject for your chosen career field such as data science or artificial intelligence. You intend to pursue a masters degree or PhD, and machine learning is a required or recommended subject. Why you should choose this instructor: I earned my PhD in Mathematics from the University of California, Riverside. I have created many successful online math courses that students around the world have found invaluable—courses in linear algebra, discrete math, and calculus. In this course, I cover the core concepts such as: Linear Regression Linear Discriminant Analysis Logistic Regression Artificial Neural Networks Support Vector Machines After taking this course, you will feel CARE-FREE AND CONFIDENT. I will break it all down into bite-sized no-brainer chunks. I explain each definition and go through each example STEP BY STEP so that you understand each topic clearly. I will also be AVAILABLE TO ANSWER ANY QUESTIONS you might have on the lecture material or any other questions you are struggling with.