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Correlation LAB in python for data science.

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Learn to calculate the correlation between variables and quantify the degree of association using correlation coefficient using the lab exercise. The video provides details on the lab exercise to explore correlation using a data set - AirTravel. Find out how the number of passengers and promotional budget is correlated, and the correlation between number of passengers and inter metro flight ratio.
For the detailed video tutorials, code files, data-sets and other material, please visit our site
Data scientist is called as the sexiest job of the 21st century.
Our "Machine Learning" course is now available on Udemy
Part 1 – Introduction to R Programming.
This is the part where you will learn basic of R programming and familiarize yourself with R environment. Be able to import, export, explore, clean and prepare the data for advanced modeling. Understand the underlying statistics of data and how to report/document the insights.
Part 2 – Machine Learning using R
Learn, upgrade and become expert on classic machine learning algorithms like Linear Regression, Logistic Regression, and Decision Trees.
Learn which algorithm to choose for the specific problem, build multiple models, learn how to choose the best model and be able to improve upon it. Move on to advance machine learning algorithms like SVM, Artificial Neural Networks, Reinforced Learning, Random Forests and Boosting and clustering algorithms like K-means.
Data science youtube playlist.
Facebook link:-
(Visit our facebook page we are sharing data science videos)
Visit our official website to go deeper into data science topics.
For the detailed video tutorials, code files, data-sets and other material, please visit our site
Data scientist is called as the sexiest job of the 21st century.
Our "Machine Learning" course is now available on Udemy
Part 1 – Introduction to R Programming.
This is the part where you will learn basic of R programming and familiarize yourself with R environment. Be able to import, export, explore, clean and prepare the data for advanced modeling. Understand the underlying statistics of data and how to report/document the insights.
Part 2 – Machine Learning using R
Learn, upgrade and become expert on classic machine learning algorithms like Linear Regression, Logistic Regression, and Decision Trees.
Learn which algorithm to choose for the specific problem, build multiple models, learn how to choose the best model and be able to improve upon it. Move on to advance machine learning algorithms like SVM, Artificial Neural Networks, Reinforced Learning, Random Forests and Boosting and clustering algorithms like K-means.
Data science youtube playlist.
Facebook link:-
(Visit our facebook page we are sharing data science videos)
Visit our official website to go deeper into data science topics.
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