6.Feature Scaling in Machine Learning(Normalization & Standardization) | Feature Scaling Sklearn

This tutorial titled "Feature Scaling in Machine Learning(Normalization & Standardization) | Feature Scaling Sklearn" explains feature scaling which is an integral part of machine learning. Since many of the times, you might have encountered a situation one of your independent variables had very small numeric values and another had very large numeric values. How to bring such column values on the same scale for more accurate machine learning prediction is something that will be covered here. This is a machine learning & deep learning Bootcamp series of data science. You will also get some flavor of data engineering as well in this Bootcamp series. Through this series, you will be able to learn each aspect of the Data science lifecycle right from collecting data from disparate data sources, data preprocessing to doing visualization as well as model deployment in production. You will also see how to perform data preprocessing and build, regression, classification, clustering as well as a recurrent neural network, convolution neural network, autoencoders, etc. Through this series, you will be able to learn everything pertaining to Machine and Deep Learning in one place. Content & Playlist will be updated regularly to add videos with new topics.

********Git Hub Link for DataSet and Python Code*********
https://github.com/nitinkaushik01/Machine_Learning_Data_Preprocessing_Python

Тэги:

#feature_scaling #what_is_feature_scaling_in_python #machine_learning_features #scaling_minmaxscaler #minmaxscaler_machine_learning #introduction_to_machine_learning #machine_learning_recipes #machine_learning_examples #machine_learning_projects #machine_learning_tutorial #how_to_do_feature_scaling #Machine_Learning_Data_preprocessing_Feature_Scaling_In_scikitLearn-1_Part-15 #Feature_Scaling_in_Machine_Learning(Normalization_&_Standardization) #feature_scaling_sklearn

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