Linear Regression


Linear Regression

Linear Regression
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 43M | 208 MB
Genre: eLearning | Language: English

Linear regression is one of the most important machine learning tools. It is the simplest of the predictive modeling techniques and it is widely used, whether on its own or in combination with other techniques. This course teaches the principles and practices of linear regression. It reviews the meaning of modeling, explains linear regression's key concepts (e.g., cost function, R-squared metric, etc.), describes the practice and need for hypothesis testing, illustrates how to implement linear regression computationally, and showcases an implementation of ridge regression. An understanding of basic mathematics is required, and some knowledge of linear algebra and differential calculus will allow the viewer to understand all of the subtle details.

Understand what regression means and how to do linear regression
Explore key machine learning concepts like cost function, F-test, and cross validation
Learn about hypothesis testing and the frequently mentioned term "P value"
Learn how to use - and enjoy free access to - the SherlockML data science platform
Develop the skills required for the machine learning job market where demand outstrips supply




Linear Regression





Download link:



Links are Interchangeable - No Password - Single Extraction

Linear Regression

Linear Regression
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 43M | 208 MB
Genre: eLearning | Language: English

Linear regression is one of the most important machine learning tools. It is the simplest of the predictive modeling techniques and it is widely used, whether on its own or in combination with other techniques. This course teaches the principles and practices of linear regression. It reviews the meaning of modeling, explains linear regression's key concepts (e.g., cost function, R-squared metric, etc.), describes the practice and need for hypothesis testing, illustrates how to implement linear regression computationally, and showcases an implementation of ridge regression. An understanding of basic mathematics is required, and some knowledge of linear algebra and differential calculus will allow the viewer to understand all of the subtle details.

Understand what regression means and how to do linear regression
Explore key machine learning concepts like cost function, F-test, and cross validation
Learn about hypothesis testing and the frequently mentioned term "P value"
Learn how to use - and enjoy free access to - the SherlockML data science platform
Develop the skills required for the machine learning job market where demand outstrips supply




Linear Regression





Download link:


Links are Interchangeable - No Password - Single Extraction
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