Different Types of Feature Engineering Encoding Techniques

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In this video we will be discussing about the different types of Feature Engineering Encoding Techniques
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Опубликовано:

14 авг 2019

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Комментарии : 685

@krishnaik06 3 года назад

Dear All, if you are looking for feature engineering materials, please check my feature engineering playlist, all videos are available. Happy Learning!

@yash20december 3 года назад

if you don't mind will u reopen the link or provide your writen codes on github with link

@krishnaik06 3 года назад

@@yash20december all materials are available in feature engineering playlist

@ulysses_grant 3 года назад

Thank you sir.

@mamtarajput9846 3 года назад

is there something more you provide for the paid ones. please let me know.

@matrix4776 3 года назад

Sir, Can you please send me the all feature engineering technique file. it will be very helpful to me, if you send them. My email id is ara007kumar@gmail.com

@prateshtamhankar3568 3 года назад

What a coincedence, today is also an Independence day, this really suprised me, I was following your youtube videos and suddenly you greeted, for a movement it got a smile on my face. Happy Independence day.

@anirvansen6591 4 года назад

Just started watching your videos. You explain the concepts in a simple manner.Thanks

@josealjndro 4 года назад

you are the best, greetings from an ecuadorian studying in Portugal.

@AkshayPatel-eq7uy 4 года назад

Thank you for putting the time and efforts to create this video, also all other videos. Very helpful.!

@sandhyas6972 4 года назад

Hi Krish, It's the best video I have ever seen. Crystal clear.

@viveksrivastavasc 4 года назад

There was doubt from so long about this that when there are more than 100 types of value then how to do encoding which is clear today thank you sir 🙏🙏

@jeevanraj1789 2 года назад

@pankajgoikar4158 2 года назад

No Words for education. Many Thanks and wishes for futures.

@sonalisrivastava9981 2 года назад

We need mentor like you... Great job👍

@robertkumar7768 4 года назад

The video is quite informative and easy to understand. I really loved the video :)

@floyd7835 3 года назад

you are doing a wonderful job Kris...👏👏

@aakashprasad3126 3 года назад

Clearly Explained, Thankyou!

@manikosuru5712 4 года назад

Thank U so much Sir for such Huge help....

@shivaaryaprakash 4 года назад

Thanks alot for sharing such a absolutely amazing knowledgeable video...

@sanyamsinghal7992 4 года назад

thanks a lot, this thing can't be explained better than how you explained it. I just became Fan of your ML knowledge.

@jeevanraj1789 2 года назад

@sam71839 3 года назад

Wao thank you soo much, sir you explained soo well. whenever I face any doubts your video saves my day.. God bless u .. Happy Learning

@NikhilSharma-rc4jg Год назад

Great Video, Thanks!

@cenobit0815 3 года назад

you saved my day with mean encoding

@anirudhr.huilgol.9449 3 года назад

Very useful information provided by u sir. Thank you.

@mr.foysalhossain2142 2 года назад

excellent job Boss. really helpful

@sagardesai1253 3 года назад

Thanks for sharing, the video is helpful!

@tech_charli Год назад

Amazing explanation sir 🙏🙏

@wordguinho Год назад

Thank you so much for sharing your knowledge with us

@salikmalik7631 3 года назад

You are the best sir.

@mahindrarao4565 3 года назад

I liked the Mean Encoding technique and Target-guided encoding. We are preserving the normality of the data as well as not increasing the dimensions.

@prakashsaravanan6613 2 года назад

Excellent Explanation Sir, Thanks a lot

@bharathjc4700 4 года назад

Please re-open the form for feature engineering techniques. Thank you.

@azharafridi9619 11 месяцев назад

thank you so much respected sir. Alot love for you from pakistan. this video was very helpfull. we are looking foreword to see others playlist like these from you. once again thanks

@deepeshkumarsharma6514 4 года назад

thanks sir for listening to my request to create a video on mean encoding , i am really enjoying your videos , and i have learned a lot from that. Please continue to create such awesome videos.

@jeevanraj1789 2 года назад

@taranilakshmi9680 4 года назад

Nice information about feature engineering. Thanks a lot

@abhaysharma3171 4 года назад

can you plz send it to me

@gajjukumar8 4 года назад

Hi krish, nice way to collect the data free of cost.

@vishalshukla2happy 4 года назад

Great help Krish... Thanks for your video man

@dollyshukla4821 4 года назад

Vishal Shukla. could you please share this docs with me on dolly.shukla7860@gmail.com

@jeevanraj1789 2 года назад

@hokapokas 4 года назад

Hey krish, nice video as usual... Filled the form and thanks for making motivational and additional support videos for encouragement. Kudos

@SanthoshKumar-dk8vs 4 года назад

Hi bro, could you please send me featuring document pls?

@hokapokas 4 года назад

@@SanthoshKumar-dk8vs you can fork it from either mine or krish's GitHub account. Check Krish's video description for his GitHub link and you find all there

@shivamkaushal4479 4 года назад

Hello bro, can you share zip file, bcz I watched it today so not able to fill form as you know. Kaushalshivam2018@gmail.com

@sarath20994 4 года назад

hi bro this is sarath.. I am a data scientist aspirant can you share me feature engineering notes.. mail id : sarath20994@gmail.com

@thakuraditi5 3 года назад

Really good one Krish

@MariaM-pu4fx 3 года назад

Great teacher. Thank you so much

@jeevanraj1789 2 года назад

@pravallikak7637 3 года назад

Krish Sir the way you explain is easy to understand. Please reopen the form. Thanks 🙂

@harshitgupta2515 4 года назад

Sir u r doing really great and I think under your guidance I will become a good data scientist soon...please help me sir

@thetensordude 3 года назад

Thanks sir for all these free contents! :p

@raakupgaming 3 года назад

Can you send the zip file to me. arifmollick8578@gmail.com

@adhipathis12 3 года назад

Thanks Krish!!!! :)

@menardtchatchou5647 4 года назад

so happy I found your channel...wooh amazing lecture Please send me the zip file with respect to feature engineering thank you sir will definitely join your channel.

@choreographer1smike 4 года назад

Amazing and easy to follow explanations! Newly subscribed and loving it! Just curious how you recover the particular categories and make sense of your results if you use something like mean encoding. Do you have to trace back the original definitions for each mean and what happens if there are repetitions?

@jeevanraj1789 2 года назад

@leadership_guru Год назад

Hi krish, thanks so much for shedding light on this topic of Feature Engineering. I'm at Beginner Level of learning DS/ML and I really fell in love with your way of teaching these techniques. I would really love to get that document on FE you mentioned about in this video. I tried to drop my details via the google form but I see it's closed. Kindly assist please. Thanks in advance!

@chetanahirrao5601 Год назад

Very good

@mushirahunt 3 года назад

Hello sir...your way of teaching is really incredible. I am studying through your lecture for past 1week and that's why unable to fill the form to get the materials which you have prepared for the same... So if possible please enable the form link again...

@akshaygupta6321 4 года назад

Krish your way of explanation is just amazing....Thanks for these amazing videos and yes please share zip file

@jeevanraj1789 2 года назад

@manishsahu3181 4 года назад

Sir, please share the link once again. I saw your video and it's a very helpful for the student's like me. I want to know more about the feature engineering. Thank you for making such an amazing lecture. Waiting for the feature engineering link.

@jeevanraj1789 2 года назад

@biggusmaximus1651 2 года назад

thank you sir from tamil

@Itachiuchiha-de9cj 3 года назад

You are awesome sir 🙏

@jeevanraj1789 2 года назад

@tahamansoor599 4 года назад

Great Video plz give demo also

@revathiboopathi8883 Год назад

Hi Krish, I have a question. So, we are normalizing all numerical fields which will make it in the range 0 to 1. While encoding categorical variables, we "one hot encode" a few which will make them either 0 or 1. However, there are a few categorical fields where we are "label encoding" as order matters. It would be encoded like 1,2,3,4,.... which is not in the 0 to 1 range unlike the first and second case that I had discussed. I would like your advice here whether I need to normalize after label encoding the data and range of this case alone won't be in 0 to 1 and normalizing would make it in 0 to 1 range.

@rojaroja9913 4 года назад

Thank You Sir!!things we can understand easily by your Videos.Sir could you pleasee reopen the link where we could get the Feature engg materials that could be more great

@vininitdgp 3 года назад

nice one

@davidibrahim874 2 года назад

Thank you so much Kris, your videos have been instrumental in my learning process. However, I wanted to find out if it were too late to get the feature engineering code. As it mentioned, the link was opened fir two days hence its been over a year. Or if you have it on your git, I can get it too. I've been struggling with feature engr, though I'm still learning, having that code would mean alot to me. Thank you so much in advance

@durgakorde3589 2 года назад

Thanks

@jackshaak 2 года назад

Hi Krish, thanks for this very good video. Just to clarify a bit, when you say Pincode, are you referring to the postal or zipcode? Because from where I am, when they say pincode it means bank's pass code or something like that.

@VARISHROCKS 2 года назад

Sir , Thankyou for this wonderful lecture , please share the study material

@SimoneIovane 4 года назад

I agree with all the encoding you treated, however I got doubts on assigning an ordinal label based on the mean value of the output. By doing this you are setting the distance between levels to one, while in reality, based on the output mean, some level might be close than others, with distances less than or more than 1. What do you think? I would also point out the risk of data leak in case of mean encoding, for this reason I'd add a random noise to the mean

@bsrinivas2510 4 года назад

Awesome

@shubhammishra8686 4 года назад

Thanks Krish Bhai..I have learned a lot from your videos

@baneledludlu7983 Год назад

Thanks man! Great content The Lord bless you with more understanding and help you to know Him better and better

@sindhuranimmaraju7392 4 года назад

Hi I already joined as a member

@jackdairies2live400 4 года назад

Hi krish, I started seeing your videos now and want the feature engg doc. Can you please open the link for the form? Waiting for your response.

@vidulakamat6564 4 года назад

This is very informational video. I would like to go through the feature engineering material mentioned here. Will it be possible for this material to be available?

@TheWonderYearsSchool 3 года назад

Hi. Happy New Year Krish. Your content is awesome. Can you pls reopen the link to the encoding document?

@nadellagayathri 4 года назад

Hi Krish, I have started liking your channel so much. Hats off for the great service you are doing for the aspiring and already experienced Datascientists. The form url which you have shared is no more available. Could yuo please share the material via google drive or reactivate the form.

@Itachiuchiha-de9cj 3 года назад

Guys plz if u don't like his videos then leave it, but don't do dislike 🙏

@ChandraManiPandey1412 4 года назад

@StaySwasthh 4 года назад

Hello Sir, could you please open the google form link, i need those feature engineering code snippets, it would be of great help.

@antrikshsingh7798 4 года назад

Hey awesome video there. Just one doubt in the KDD orange competition. They came up with top 10 categories. How exactly did they arrive at the figure 10? Isn't covering certain variance of total categories would have made more sense? What I mean is, let's say if there are 40 categories in a column and if I select 12 categories that covers a total of 80 percent or 90 percentage of all rows. Wouldn't that make more sense rather than choosing static figure of 10.

@arvindsaini6678 3 года назад

Hi @Krish, can you please share the Feature engineering materials if possible. Your videos are really impressive.

@gordongogah5376 4 года назад

I came across this video today and i like to learn more feature engineering "if you don't mind will u reopen the link sir"

@nemesisanims7401 4 года назад

Yes pleaseeee

@karthikeyans1646 4 года назад

Yes please sir reopen

@siddhantpathak6289 4 года назад

Yes, it's very much needed now

@sarveshkhetan4241 4 года назад

yes please sir

@priyabratapanda1216 4 года назад

It's on the GitHub

@gautamr5976 4 года назад

In case of mean encoding and Target guided methods, how will i calculate the mean value when i have hundreds of class in the dependent variable to be predicted? (considering many-many relationship of categorical value of a feature with dependent classes)

@sandipansarkar9211 2 года назад

finished watching

@sandeepnataraj2430 4 года назад

Good one Krish. How do you mean encode variables from the test set ?

@belloahmadmuhammad685 4 года назад

I came across this video today and i like to learn more on feature engineering "if you don't mind would u reopen the link sir"

@deviprasadmishra805 4 года назад

Sir please could you please tell us why the theory of computation is actually used and what are the application of these subjects please Sir make a video on that

@user-xw5le5yd3t 7 месяцев назад

Hi Krish , I really liked the way you are teaching, could you please share the feature engineering study material?

@shaktiprasadmishra5239 4 года назад

Hi krish, Today only I saw this video.could you please kindly open that Google forum one more time.

@arunporky 3 года назад

Hi sir. I have started to learn ML from your channel only. Thank you for your knowledge that you are sharing with us. I also have one request for you can i get feature engineering zip file now. I am really interested in ML.

@sandyjust 4 года назад

@16:18 position you are saying to use 'one-hot encoding with multi-category' for an ensemble technique. But the beginning of the video you had explained ensemble techniques does not require feature scaling. Can you please clarify?

@MrJaga121 4 года назад

Hi Krish , Mean value will be replace with the category variable values in Mean encoding . will the same apply for o/p as numeric values . If the target variable is number , calculated mean will replace by categorical variable values ?

@adeyanjumusliyu5086 Год назад

Krish naik you have been so helpful to me on this journey to datascience. The form is no more available is there another way for me to get the feature engineering and again about the Patreon are you still running it or it's already closed?

@adityasingh788 4 года назад

Hi krish, I just saw your video and you have mentioned that the link is available for two days only. Is there any possibility that I can get the materials/files ?

@AbhishekKumar-jv3fe 4 года назад

Hi Krish ..... I had recently started to follow up your video & it was very helpful. could you please provide me the materials related to feature Engineering......thanks in advance

@490sivasasi3 4 года назад

I would like to learn something about it "will u reopen the link sir"

@rahuljaiswal9379 4 года назад

Hey Kris u r awesome 😎 dear, u have boost my knowledge n conference. I m not able to get ur shared material, so please can you help me with this 🙏

@nasimashujaat3264 3 года назад

Hi @Krish Bro Your link for google form is no longer available. And I must thank you for the amazing knowledge you share with us. God bless you for your good work. Trust me, I think you are the only person who can teach data science to anyone, I mean you are making it halwa for your viewers :D. I have watched almost all of your Videos. Thumbs up to you (y) .

@jeevanraj1789 2 года назад

@javeda 2 года назад

Please do a session work on the dython package and setting categories in it

@dineshkumard2765 4 года назад

The forum no longer, how do I get the material?

@sathyanarayanan1822 4 года назад

Hi sir, I need the feature engineering material sir.so please send the link Once again..your techings are awesome and clean to understand 🙂

@hichamamchtkou7343 4 года назад

Thank you Krish it is very interesting . Don't you think that using the output variable in the feature engineering part can cause the data leakage problem ( mean coding for example) ?

@jeevanraj1789 2 года назад

@sivakrishna4396 4 года назад

Could you please upload the forum again . ? Thanks in advance :)

@saumyagupta4019 3 года назад

Sir please open the form enteries to get zip file for feature engineering

@nagakalyan4971 3 года назад

In case of multi class classification and linear regression problems how we can do target guided ordinal encoding or mean encoding?

@lucyf27 3 года назад

Hi krish, I am your new subscriber. I just started learning ML 2 months ago. I learned a lot from your videos. I just have a question regarding mean encoding. I have computed the mean encodings using the training set to avoid leakage but I have issues with the encodings identified in the training set when mapped to the test set because there are cases where some categories in test set are not identified and encoded in the training set. Can you tell me how I could resolve this?

@SumitSharma-pu6yi Год назад

May be a late reply.. then give those mean encoding of 0 because they didnt occur in the training set. There is also a stratified sampling approach.

@subhankarkhandai2086 2 года назад

Sir I have a dataset 5000 rows and 36 columns. It is a mixture of both string and interger values. There are are two columns Name and Company which should be encoded. Which method would be the best?

@firta_banjara 3 года назад

Hi Krish, At 20:23 the Label for A - 0 and A - 1 will be different based on mean right ? for example the mean will be calculated this way right ? A - 1 => 0.73 B - 1 => 0.6 C - 1 => 0.4 A - 0 => 0.5 B - 0 => 0.35 C - 0 => 0.36 Then the ordering of feature will be as below right ? A - 1 >> B - 1 >> A - 0 >> C -1 >> C - 0 >> B - 0

@af121x 4 года назад

Thanks a lot for the clear explanation. Can you Please reopen the google form again?

@zeeshankhanyousafzai5229 2 года назад

Sir, I am working in Data Science for a long time but want to your all playlist as I already have covered some of them. I need your notes on Feature Engineering so can you provide me it now. I shall be very thankful to you for this kindness. Best wishes more love for you from Pakistan.

@jeevanraj1789 2 года назад