Introduction to Machine Learning

This “Introduction to Machine Learning” course will give you a detailed introduction to the fundamental concepts of machine learning. Here you will be taught all about the popular machine learning algorithm in detail. The instructor will be covering all the standard and most popular supervised learning algorithms. This includes linear regression, logistic regression, decision trees, and much more. With that, you will get a detailed introduction to Bayesian learning and the Naïve Bayes algorithm. Going further, the instructor will be explaining in detail the basic clustering algorithms. You will understand the reduction methods in a step-by-step guide. Then the instructor will discuss the different issues relevant to the application of machine learning algorithms and so much more in detail.

What will you learn in this course?

If you enroll in this course, you would for sure learn a lot of things about Machine Learning.

• First, you will get a detailed introduction to Machine Learning.
• Then the instructor will talk about linear regression and overfitting in detail.
• After that, you will understand what instance-based learning is.
• Then you will understand all about the collaborative filtering-based recommendation.
• Moreover, the instructor will talk about probability and Bayes learning in detail.
• Next, you will understand what a support vector machine is.
• After that, the instructor will give a detailed introduction to deep neural networks.
• You will understand what backpropagation is.
• Then you will learn about multilayer networks.
• After that, you will get a detailed introduction to computational learning theory.
• Next, the instructor will talk about the PAC learning model.
• After that, you will understand what adaptive hierarchical clustering is.
• Then you will learn all about the Gaussian mixture model.

Therefore this and many other things about Machine Learning will be learned in this course.

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