Log Transformation for Outliers | Convert Skewed data to Normal Distribution

This video titled "Log Transformation for Outliers | Convert Skewed data to Normal Distribution" explains how to use Log Transformation for treating Outliers as well as using Log Transformation for Converting Positive Skewed data to Normal Distribution form. Code example in Python is also covered in the video. 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.

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[TheAIUniversity]

What are the other techniques
I can use to treat outliers or convert negative or positive skewed data into normal distribution form?

[nabeelnaseer]

What can we do if even after the transformation, there are outliers..am kinda puzzled over this notion of natural outliers. Like we are supposed to treat them separately.. can you give some pointers..

[aakashv]

What are the functions to be applied for negative skews and also if the data has zero

[mansirawat]

Suppose in one of my outcome measures pre is normal but post is not normal, so should I log transform only the post recording or should I transform both the pre and post values for further analysis?

[shrutimadan]

using log10 transformation, it didnt give normal distribution.
How to deal with this?

[ajaykushwaha-jemw]

Sir what is the correct sequence of variable transformation.
First we need to do feature scaling then Gaussian transformation or First Gaussian transformation then feature scaling ?

[vinayvvalaboju]

Can you fix a custom bin And filter data til upper quartile.

[creativesurgeinfidel]

Thank you.. Could you please let me know how to convert natural log back to the original value

[balamurali]

Sir small dout I have two variables(independent and Dependent) represented in percentage. If I apply log for only one variable. Will result differs. Is it the correct way of transformation/analysis

[pallavijagtap]

Sir, Once you transform the variables, do we have to use same transformed columns in further process of melling?

[pallavijagtap]

Pallavi Jagtap
1 second ago
Sir, Once you transform the variables, do we have to use same transformed columns in further process of modelling?

[MrNabiwishes]

Log transformation applied to train set, and when out of sample data comes in do we apply same transformation...

[amitbudhiraja]

I have a doubt like what is the optimal method to do remove the outliers [Z-score, IQR method] or use transformation methods like log normal or inverse 
Can someone tell ?

[aniketsultan]

other methods square root, cube root, binning

[elyasmohammadi]

Hello and thank you for this nice video.
Could you please clarify that what are the axis X and Y before and after log transformation. Thank you in advance

[durgadeviarulrajan]

Hi, Thanks for the great video. Is it necessary to convert all features into normally distributed, before modeling? Is it a compulsory step to follow in feature engineering?

[ankurkamthan]

Why should not taken log with base e and y base 10

[independent]

negatively skewed data to normal distribution?

[nikhilgaikwad]

after we transformed the column values using log10. if we build a app using flask what values we should pass for that column to predict the output?? the original value or first we need to transform that value using log 10 and then insert??

[nicholaslipanovich]

The information you communicated to us was fine but your delivery could use some work. Trying to repeat yourself less might help.