Simple Linear Regression | Scikit Learn & Spark MLLib | Model Evaluation Techniques - Part 1

preview_player
Показать описание
This video titled "Simple Linear Regression | Scikit Learn & Spark MLLib | Model Evaluation Techniques - Part 1" of Simple Linear Regression using Scikit Learn and Spark MLLib Series explains R-Square and Adjusted R-Square techniques of Evaluating Regression Family of Algorithms/Models. Implementation through Python is also covered.

FOLLOW ME ON:

About this Channel:
The AI University is a channel which is on a mission to democratize the Artificial Intelligence, Big Data Hadoop and Cloud Computing education to the entire world. The aim of this channel is to impart the knowledge to the data science, data analysis, data engineering and cloud architecture aspirants as well as providing advanced knowledge to the ones who already possess some of this knowledge.

Please share, comment, like and subscribe if you liked this video. If you have any specific questions then you can comment on the comment section and I'll definitely try to get back to you.

*******Other AI, ML and Deep Learning Related Video Series*****

******************************************************************

#ModelEvaluation #SimpleLinearRegression #ScikitLearn
Рекомендации по теме
Комментарии
Автор

Trivia question from the video: What does the parameter "p"
signify in the Adjusted R square equation ?

TheAIUniversity
Автор

what is the difference and Uses between R-Square, Adjusted R-Square and RMSE( Root Means Square Error), Mean Square Error ( MSE), Mean Absolute Error ( MAE). Also, It would be great, If you can Explain with Examples.

punyashloke