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@srikanthkuchi7743

5 жыл бұрын

Thank you so much

@kamakhyasingh9994

4 жыл бұрын

It's an awesome explanation, Thank you very much, Please share the source code & datasets to my mail id : rkamakhya@gmail.com

@sanatansuryavikram

3 жыл бұрын

Shrey 1 second ago hi what if the labels , dependent variable is 7 and 8 do you have to change it to 0- and 1 or do i keep it as it is to perform logistic regression pleas reply asap.

@edurekaIN

3 жыл бұрын

Hi Shrey, it has to be dichotomous. So if there are only two categories, you can transform the labels. Hope that solves your query.

How do you speak so flawlessly without fumbling or pausing even for once. Hats off.

Excellent explanation. The way you prepare PPTs to explain the concepts is matchless in the industry. keep it up.

In the world full of greed no one is providing knowledge for free. Edureka you are doing great job 👍

Just to clear my concept on logistic regression i searched L R and saw this video. It is perfectly explained by the instructor. Each and every part is well explained. Glad to see this video. A big thumbs up👍 and Thanks.

This one hour video has given immense clarity and confidence. Thanks team!

You guys are awesome! Explained the concept very clearly and in an understandable way. Thanks a lot!!!

Thank you mam.. got all the concepts...

God bless you, Thank you so much for this

"Over here" great job! 👍🏻

Great explanation within a short span of time.This lecture has been very helpful.Thank you mam!

Great video and a very thorough and clear explanation . Helpful session for the day . Thanks a lot !!!

Awesome! Really liked it. Live presentations are never this good.

Thank you mam for vaulable class on logistics regrations and it gives a clear underatanding to me for alogirthms development in ML

Thank You, This tutorial is Very Nice

Thx u. Very clear instruction

It's so understandable lesson! Thank you.

Loved the way the lesson is taught.

Thank You, its a very helpful Video. Like to share share 2 points - 1) In Code line # 63 I could not import cross_validation from sklearn library, so I substituted with 'from sklearn.linear_model import LogisticRegression' and then it worked 2) I dropped "Fare" column and it gave a 100 % accuracy on test data !

Mem your teaching skill is excellent You explain point to point and in detail. #thnx for making this video

You are very very efficient speaker and have delivered great analysis.. thank you

Very good explanation for each line of code. Loved it

Thanks Edureka got all the concepts cleared.

Best explanation on regression so far thank u so much

Thanks you madam it very clear cut explanation

Thank you so much ma'am. Really its a great tutorial.

Thanks Edureka....your videos are of high quality ...

Thanks a lot, Sister. Keep it up.

well explained , My concepts about logistic regression have cleared . Thank you

@edurekaIN

5 жыл бұрын

Hey Bilal, we are glad you feel this way. Do subscribe and hit the bell icon to never miss an update from us in the future. Cheers!

very well explained ,thank you for such good explanation...

thank you ma'am.. keep it up

Thank you Madam! very good explanation

this is awesome my concept of logistic regression is clear now

Thank you, This is very helpful for my studies.

@edurekaIN

4 жыл бұрын

Thanks Suresh!

Thank you soo much very nice class

The video is very nice. The way our concepts are getting cleared. Please give us the link to download the notebook which you created as titanic.

very clearly explained.Hats off Mam

helpfull..thnku

Thank you... Really helpful.

perfect !! freaking awesome !!...subscribed

@edurekaIN

5 жыл бұрын

Hey Matitiude, thanks for subscribing! We are glad you loved the video. Do take a look at our other videos too and stay tuned for future updates. Cheers!

Amazingly defined 👍 Thankyou

A very helpful video.Thank you for the brief tutorial on using Jupyter notebook.

@edurekaIN

5 жыл бұрын

Hi Aditya, thank you for watching our video. Do subscribe, like and share to stay connected with us. Cheers!

Best explanation on logistic regression thank u so much..

Wonderful explaination. 👏👏

Great session! Thank you :)

Thank you for such a wonderful lesson!

thanks for video...liked it

Nice video,more way of wrangling the data to view NA : titanic_data.isnull().any()

Hi , your work is very help full and Thank you. But I was wandering how I can do a prediction for new data set which is not labeled (0 and 1) by using my trained machine and store it to excel.

@edurekaIN

5 жыл бұрын

Hey Niguss, please do check this link to know more. www.jmp.com/support/downloads/pdf/jmp902/modeling_and_multivariate_methods.pdf

very much useful it is. thank you

Explanation is tooo good.... Thnkz alot😊

I really felt very happy with your explanation, very useful for begginers

@edurekaIN

Жыл бұрын

Glad it was helpful! Keep learning with us .

You Guys are awesome.

best explanation of logistic regression

Hello Can you also make a video on how to plot these predicted values.

@edurekaIN

6 жыл бұрын

Hey Vivek, we will definitely look into your suggestions. We update our channel regularly, stay tuned and never miss out on our updates. Cheers :)

One of the best videos in detailed.thanks a lot

@edurekaIN

5 жыл бұрын

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

Thanks, really helpful

Very well explain. Keep it up Edureka! Team

Great explanation,pls share me the datasets

I really like ur explanation mam!! I have got answers for so many doubts with ur explanation. Can u please tell me where to find this excellent notes?? Want more videos on ML😊

@edurekaIN

5 жыл бұрын

Hi Yashwanth, Thanks for the compliment. We are so glad to hear that you liked our videos. You can always refer to the Machine Learning Playlist of Edureka for more such helpful videos. Here's a link to the playlist kzread.info/dash/bejne/gp5k0MeShdOfhMY.html

Very well explained. The explanations are precise as well as on the point. Thank you. p.s: can you please provide the link to the dataset?

great efforts!! can you share the dataset?

Thankyou ...was able to understand all the concept

@edurekaIN

3 жыл бұрын

Thank you so much for the review ,we appreciate your efforts : ) We are glad that you have enjoyed your learning experience with us .Thank You for being a part of our Edureka team : ) Do subscribe the channel for more updates : ) Hit the bell icon to never miss an update from our channel : )

Hi, presentation is really good. Anybody can understand it easily. Thanks for such wonderful lecture. Input: Our prediction can go to ~ 82% if we can fill the null values in 'Age' column with average values and can be done by 2 methods. 1) Fill the null values with the value which is the average of all age. (df['Age].mean(). Where df variable name for our dataframe) 2) Fill the null values by taking the average values with respect to column 'Pclass'. Example: If average age of passengers travelling in 1st class is taken and fill the null values with respect to 1st class. Same is done for 2nd and 3rd class. Average age with respect to 'Pclass' can be assumed from the boxplot of seaborn with 'Age' as x and 'Pclass' as y. Method 2 is better over method 1. Look at the code to fill the null values in 'Age' with respect to 'Pclass'. (train is the variable name of dataframe) ********************************************************************************* def impute_age(cols): Age = cols[0] Pclass = cols[1] if pd.isnull(Age): if Pclass == 1: return 37 elif Pclass == 2: return 29 else: return 24 else: return Age train['Age'] = train[['Age','Pclass']].apply(impute_age,axis=1) ******************************************************************************* My prediction is as follows: Accuracy: 82.02247191011236 ******************************************************************************* Classification Report precision recall f1-score support 0 0.81 0.93 0.86 163 1 0.85 0.65 0.74 104 micro avg 0.82 0.82 0.82 267 macro avg 0.83 0.79 0.80 267 weighted avg 0.82 0.82 0.81 267 ******************************************************************************* Confusion Matrix: [[151 12] [ 36 68]] ******************************************************************************* Predicted 0 1 Actual 0 151 12 1 36 68

Nice video..Please provide the data set

Wow. Great explanation

Simply wow. Excellent explanation by you mam. We need professors like u.

@edurekaIN

2 жыл бұрын

Hi : ) We really are glad to hear this ! Truly feels good that our team is delivering and making your learning easier :) Keep learning with us .Stay connected with our channel and team :) . Do subscribe the channel for more updates : ) Hit the bell icon to never miss an update from our channel : )

very useful real case example

Thanks for giving simple short and meaning full information.Thanks

@edurekaIN

5 жыл бұрын

Hey Raja, Thank you for appreciating our efforts. We are glad you loved the video. Do subscribe, like and share to stay connected with us!

Explained very clear, need to go bit slow.

Thank you so much.

Wonderfull explanation..thanq edurekha 🙂 can u pls share me the datasets plz...

Thank you mam ,your video very clear ,good help us

@edurekaIN

5 жыл бұрын

Thanks for the compliment Yasmin, 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!

@shaikyasmin2559

5 жыл бұрын

@@edurekaIN OK mam

wow very rich in content explained well

Thankyou Soooooo Much Ma'am!!!!!!

After many videos , I got a nice explanation. Kudos to you mam ❤️

@edurekaIN

2 жыл бұрын

We are super happy that Edureka is helping you learn better. Your support means a lot to us and it motivated us to create even better learning content and courses experience for you . Do subscribe the channel for more updates : ) Hit the bell icon to never miss an update from our channel : )

Thank you so much 😍😍

Thank you!

You did an excellent job, thank you very much!

@edurekaIN

2 жыл бұрын

You're welcome 😊 Stay connected with our channel and team :) . Do subscribe the channel for more updates : ) Hit the bell icon to never miss an update from our channel : )

Thank u..😇

Very much helpful mam🤗

Thanks for this great video. Very helpful.

@edurekaIN

5 жыл бұрын

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

can you provide dataset along with tutorial ? or link to get it? on kaggle many datasets are there with 'titanic' name

@edurekaIN

Жыл бұрын

Hi ! Good to know that our videos are helping you to learn better 😊 Please share your mail id to share the data sheets, We’ll update you soon . Do subscribe the channel for more updates.

My goodness! How did you get this good at teaching. 👏👏👏

@edurekaIN

2 жыл бұрын

You're welcome 😊 Stay connected with our channel and team :) . Do subscribe the channel for more updates : ) Hit the bell icon to never miss an update from our channel : )

It was a good video in titanic dataset, mean should be taken for age column instead of dropping na. Overall, the video was good and nice explanation.

@edurekaIN

4 жыл бұрын

Thank you for appreciating our efforts. We are glad you loved the video. Do subscribe to our channel and stay connected with us.

Great explanation 👌 👍 👏 😀

Tremendous work with this presentation and project.

@edurekaIN

2 жыл бұрын

Thank you for your review : ) We are glad that you found our videos /contents useful . We are also trying our best to further fulfill your requirements and enhance your expirence :) Do subscribe the channel for more updates : ) Hit the bell icon to never miss an update from our channel : )

One of the best tutorial ever,Mam can you pls share the dataset and source code...Thank you.

@edurekaIN

5 жыл бұрын

Hey Kamlesh, we are glad you loved the video. Do mention your email ID over here and we will send the files to you. Cheers!

Please make tutorials on path planing in robotics and practical implementation

mam love you . . .! simply awesome . . .!

why you have used the Standardscalar function in the SUV model , what is the actual use of it ?

@edurekaIN

5 жыл бұрын

Hi Anshika, Scalers are used to scale the values of predictor variables along the same range in order to avoid biasness.

very good explanation

very good tutorial

GREAT EXPLANATION MAM

Outstanding explanation. I am pursuing AI Silver from Pixel Tests but your way of explanation is by far the best one. Thanks for sharing your knowledge. Sharing is caring indeed.

@edurekaIN

Жыл бұрын

We are very glad to hear that your a learning well with our contents 😊 continue to learn with us and don't forget to subscribe our channel so that you don't miss any updates !

Thank you so much! Very helpful!

@edurekaIN

2 жыл бұрын

Good To know our videos are helping you learn better :) Stay connected with us and keep learning ! Do subscribe the channel for more updates : )

Best explanation ever

hi ,your video is nice ,provide data sets for both the examples that you have discussed..

@mohanraogorapalli4735

5 жыл бұрын

email id: mohanraogorapalli@gmail.com

Thanks for your video. It makes life easier.

@edurekaIN

2 жыл бұрын

Glad it helped!

Thank you for the clear explanation. Can you please provide the datasets and the python notebook used in the video?

@edurekaIN

4 жыл бұрын

Please mention your email id (it will not be published). We will forward the dataset to your email address.

@aishasiddiquadabeer5143

4 жыл бұрын

@@edurekaIN my email id is myskillcentral@gmail.com