Data Science and Machine Learning Series Closed Form Solution of Linear Regression and Locally Weighted Regressions (LOWESS)

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Video: .MP4, AVC, 916x514, 30 fps | Audio: English, AAC, 44.1 KHz, 2 Ch | Duration: 1h 46m | 255 MB
Instructor: Advait Jayant

Follow along with machine learning expert Advait Jayant through a combination of lecture and hands-on to apply the Closed Form Solution of Linear Regression and Locally Weighted Regressions (LOWESS).

The following four topics will be covered in this Data Science and Machine Learning course:

Introducing Closed Form Solution of Linear Regression. Be able to explain the Closed Form Solution of Linear Regression in this first topic in the Data Science and Machine Learning Series. Follow along with Advait and perform the derivations necessary to understand this powerful algorithm.
Implementing the Closed Form Solution of Linear Regression using Python. Implement the closed form solution of linear regression using Python in this second topic in the Data Science and Machine Learning Series. Follow along with Advait and start by importing the numpy, pandas, and Matplotlib Python libraries.
Introducing Locally Weighted Regressions (LOWESS). Be able to explain the Locally Weighted Regressions (LOWESS) algorithm in this third topic in the Data Science and Machine Learning Series. Learn how it is different than linear and multivariate linear regression.
Implementing the Closed Form Solution to Locally Weighted Regressions (LOWESS) using Python . Implement the closed form solution to Locally Weighted Regressions (LOWESS) using Python in this fourth topic in the Data Science and Machine Learning Series. Follow along with Advait and start by importing the numpy, pandas, and Matplotlib Python libraries.
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