Scikit Learn Tutorial | Machine Learning with Python | Python for Data Science Training | Edureka

[@edurekaIN]

Got a question on the topic? Please share it in the comment section below and our experts will answer it for you. For Edureka Python Machine Learning Course curriculum, Visit our Website: bit.ly/2OpzQWw

[@amitgupta3320]

I am Truely a big fan of EDUREKA now .........

[@edurekaIN]

Hey Amit, that is delightful to hear! We always try our best to serve avid learners like you. Do subscribe and stay connected with us. Cheers :)

[@kinggRafi]

train_test_split is now model_selction , not cross_validation

[@edurekaIN]

Yes, you are right.

[@navinpandey1309]

Thank you

[@narsinhakulkarni9167]

Most helpful content which I found on KZbin...Thanks!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

[@edurekaIN]

Thanks for the compliment, Narsinha! We are glad you loved the video. Do subscribe to the channel and hit the bell icon to never miss an update from us in the future. Cheers!

[@gajendrap.s.raghava6421]

Excellent lecture crisp and clear

[@pubudithamanathunga812]

Thank You. This tutorial was very informative as well as being easy to understand. Please Keep It up !

[@edurekaIN]

Hey Pubuditha, we are glad you loved the video. Do subscribe to the channel and hit bell icon to never miss an update from us in the future. Cheers!

[@srikanvs582]

can u say the process of converting data to 1d ithout using ravel function?

[@joysanimationstudio2375]

thanks for this!!

[@shubhamsahai2492]

Very nice session. Thank you!

[@tejasonly]

Edureka rocks!

[@shoaib_zubair]

thank you for this awesome stuff.

[@karthikc7288]

Thank u mam..it is nice.

[@GeminiLearning]

This was very concise and informative. Thanks a lot my sister

[@edurekaIN]

Thank you for watching our video. Do subscribe, like and share to stay connected with us. Cheers :)

[@san2007iit]

Thanks a lot, Edureka .. such a nice video explaining tough concepts in a simple manner..Helping in my research work..

[@edurekaIN]

Hey Sandeep, we are glad to have helped. Do subscribe and stay connected with us. Cheers :)

[@aparnadevkate2935]

In SVM hyperplane separates data points into two parts buts there are three classes of iris , how can we separate three types of data points using single hyperplane ?

[@edurekaIN]

Hey Aparna! Yes, SVM can be used for multi-class classification. Though it works on binary separation using maximum margin you can think of taking one class at a time and maximising the distance from all the rest, treating the rest as a single class. That is basically how a one vs all classification works. Hope this is helpful. Cheers!

[@akshaysunil2852]

Can we do the same in pycharm IDE

[@edurekaIN]

Yes, you can.

[@JaikrishnaSharma]

Where I can find the video for Decision Tree, Random Forest and Naive Bayes Classifier?? Please share the link.

[@edurekaIN]

Hi Jai, please to these links: kzbin.info/www/bejne/pqSro5aJlsiIb7s, kzbin.info/www/bejne/nZ7Qh2eap7WHiZY, kzbin.info/www/bejne/p3XGnWB8h9Oqibc.

[@hachidori9]

For the prediction accuracy score, I got 0.6666666666666666 .... but the instructor got 0.9666666666666667 ... did anybody else have this issue? I'm trying to figure out if I've made an error.

[@hachidori9]

I was able to figure it out. I had made adjustments to the coding due to using a different IDE platform (Pycharm) .. and had added the lab_enc = preprocessing.label.LabelEncoder(). I removed that and it works perfectly now.

[@ravikrishnarpan]

I want to join

[@edurekaIN]

Hey Ravi, thank you for watching our video. Check out our course here, you will find this very interesting: www.edureka.co/data-science Hope this helps :)