Machine Learning with Python video 7:How to Handle Categorical Data||OneHotEncoding||ColumnTransform

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In this video i will show you how you can handle categorical data . it will be done in two steps
1) LabelEncder to give numerical value to each category
2) one hot encoding and column transform to give each category a separate column
How do I encode categorical features using scikit-learn?

related video title:
Future of AI/ML | Rise Of Artificial Intelligence & Machine Learning | AI and ML Training | Edureka
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Комментарии
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Why do we need to do Label Encoding before the column transformer step? Can't we just use ColumnTransformer with OneHotENcoder only? without using Label Encoder?

vinayraghunath
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I paid an Udemy course that couldn't explain this topic, you help me a lot man I'll follow your course for sure

jesusm
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thanks man! helped a lot! All old tutorials show old sklearn libraries. Very tough to excute when you are a beginner in ML

lopamudrachandra
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how to decode ? I stucked in such a situation where I need decoding after encoding

chandanramani
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Great video
How do we retrieve column names for the final dataframe

okwuazuifeanyi
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Please do video explaining KNN and random forest is possible as well

aodhan
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Very nice but what if I have 10 or more categorical features and each feature with 20-30 categories in it. How should I tackle that kind of data?

JainmiahSk
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Hi, may i know how we can use columntransformer if we need to apply the one hot encoding multiple columns at once

nivednambiar
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sir, I need your help I am working on English premier league prediction so my target variable is Full-time result(FTR) and FTR have a categorical value that is H, A, and D so how to handle that kind of problem if our target variable is a categorical value like H, A and D, H means Home and A means Away and D means Draw

ameerhamza-zroc
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Very great and clear work you have done. i have a question please, i am working on my raster dataset for prediction like ANN, RF and CNN, i have converted the rasters into numeric and then train and test the data and got very good accuracy. Now i need to convert my test data into raster again as final prediction map but i don't know how to do this, please guide me thanks.

umairrasool
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yes sound is too low. I had to use headphones.

kaustubhdwivedi
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awaaz badha le bhai full volume pe bhi nhi aa rhi awaax tumhari

chichagg
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please use good microphone .. otherwise all good

gusionfusion
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sir tumara sound chimani gat hai thoda kavleki tara karo means bada

kaivalyabhosale
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Instead of df[:, 8] = couldn't we just state df['origin'] ? When we want to transform/work directly on the dataframe, not the array. Actually could you redo this video working directly on dataframes NOT arrays...

cboyda
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O bhai your voice sound is too low.. Seems like you are making video under pressure of talibanis

pradeeprajpoot
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Madame ji thoda tez nahi bol Sakti kya app

MadhukarMishra