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this is undoubtedly one of the best, precise and to the point tutorial videos on any learning site! I've tried many videos, but this has by far taught me the most! thanks so much!
WooHoo! We are so happy you love our videos. Please do keep checking back in. We put up new videos every week on all your favorite topics. Whenever you have the time, you must also check out our blog page @simplilearn.com and tell us what you think. Have a good day!
Machine Learning is the Future and yours can begin today. Comment below with your email to get our latest Machine Learning Career Guide. Let your journey begin!
Hi, thanks for watching our video. We have sent the requested dataset to your mail ID. Do show your love by subscribing to our channel using this link: ruclips.net/user/Simplilearn and don't forget to hit the like button as well. Cheers!
@@SimplilearnOfficial Thank you very much for the video. Excellently presented! Please send me the salary csv file to niktik7@gmail.com. Thanks once again.
Best Explanation I have ever seen of this topic..!!!!!Can u plzz send me the dataset andother attachments to my mail id as soon as possible..MAIL ID dixit.devraj007@gmail.com
Very nice! I'm taking a Machine Learning class on Coursrea and after watching this, I understand more of how to implement the algorithms. The class actually got me confused on how to apply it to daily tasks/projects. Now I have some projects in mind. :D
Glad it was helpful! Do show your love by subscribing to our channel using this link: ruclips.net/user/Simplilearn and don't forget to hit the like button as well. Cheers!
Thank you sir for providing such a comprehensive knowledge on ML algorithms. I would like to share that the portion covered in this video is what is asked in most of the data analysis ML interviews. this basics are the building blocks to grow upon.
I subscribed your channel for I like your explanation and your response for providing the dataset for each person separately and reading every comment & solving their doubt's.
Hey Prashanth, thank you for appreciating our work. We are glad to have helped. Do check out our other tutorial videos and subscribe to us to stay connected. Cheers :)
in linear regression python example when visualising test data you used x_train for predict option . i think you should use x_test . can you explain this please?
I believe in it one day we have the robots around us,which Can learn and do new opportunities for better solutions for All the part of technological Life.
Thank you for choosing us as your learning partner. We are thrilled to hear that you enjoyed your experience with us! If you are looking to expand your knowledge further, we invite you to explore our other courses in the description box.
We're thrilled to have been a part of your learning experience, and we hope that you feel confident and prepared to take on new challenges in your field. If you're interested in further expanding your knowledge, check out our course offerings in the description box.
at 25:32 it should have been plt.plot(x_test,lr.predict(x_test),color = 'red') right? But x_train is considered.However chart looks almost same.Dont know how.
Hi Mohan!!! You must be aware our Simple Linear Regression model has been trained on the training set data (lr.fit(X_train, y_train)). We obtained a unique equation which is the simple linear equation for those set of training data points. Since our model is trained on the training set, whether we keep train set or test set data while visualizing the test set results, it won't make any difference. We'll obtain the same regression line. To learn more on Linear Regression, refer to the following video: ruclips.net/video/NUXdtN1W1FE/видео.html
Glad you enjoyed our video! We have a ton more videos like this on ruclips.net/video/ukzFI9rgwfU/видео.html. We hope you will join our community by subscribing to our channel.
Thank you for the appreciation. You can check our videos related to various technologies and subscribe to our channel to stay updated with all the trending technologies.
Hey Michael, thank you for appreciating our work. We are glad to have helped. Do check out our other tutorial videos and subscribe to us to stay connected. Cheers :)
Hello, thanks for viewing our tutorial. It would be helpful if you will provide your email ID to us so that we can send the requested dataset promptly. On the off chance that you need your email ID to be kept hidden from others, we can do that too. Hope that helps.
Hello, thanks for viewing our tutorial. It would be helpful if you will provide your email ID to us so that we can send the requested dataset promptly. On the off chance that you need your email ID to be kept hidden from others, we can do that too. Hope that helps.
Greetings! Thank you for your kind words. Spread the word by liking, sharing and subscribing to our channel! Cheers :). You can also explore our playlists for more Machine Learning - ruclips.net/video/ukzFI9rgwfU/видео.html.
WooHoo! We are so happy you love our videos. Please do keep checking back in. We put up new videos every week on all your favorite topics. Whenever you have the time, you must also check out our blog page @simplilearn.com and tell us what you think. Have a good day!
Hello, thanks for viewing our tutorial. It would be helpful if you will provide your email ID to us so that we can send the requested dataset promptly. On the off chance that you need your email ID to be kept hidden from others, we can do that too. Hope that helps.
We're so glad that you enjoyed your time learning with us! If you're interested in continuing your education and developing new skills, take a look at our course offerings in the description box. We're confident that you'll find something that piques your interest!
Thank you so much for this wonderful online turtorial, I am a beginner to ML and this tutorial are so helpful. May I ask where can I get the data that has been used in this video for practice? Thank UUUU!
Hello, thanks for viewing our tutorial. It would be helpful if you will provide your email ID to us so that we can send the requested dataset promptly. On the off chance that you need your email ID to be kept hidden from others, we can do that too. Hope that helps.
I have a small query in a linear regression where we are first plotting the points of the train data and test data using the linear regression object to verify if both we are testing for both why? we can do it for only testing right as we are calculating the error for only test data
Hi Prasanth, you need to plot the points first for training data and then after you build the model, you need to verify it with test data points. Hope that helps!
We are glad you found our video helpful, Debanita. Like and share our video with your peers and also do not forget to subscribe to our channel for not missing video updates. We will be coming up with more such videos. Cheers!
Hey Majuren, thank you for appreciating our work. We are glad to have helped. Do check out our other tutorial videos and subscribe to us to stay connected. Cheers :)
Hello Jahid, thanks for viewing our tutorial and we hope it is helpful. It would be helpful if you will provide your email ID to us so that we could send the requested dataset promptly.
Very nice lecture with good example. Thank you Simplilearn. By the way I have got my PMI Risk Management Certification through you. Can you please send me the ML algorithms? Thank you again
Hello Nik, thanks for viewing our tutorial and we hope it is helpful. It would be helpful if you will provide your email ID to us so that we could send the requested dataset promptly.
Great that you liked the tutorial, Krzyazlof! If you agree that Machine Learning is good career move, Please refer to this, www.simplilearn.com/big-data-and-analytics/machine-learning-certification-training-course.. Also, Subscribe to our channel by clicking on the bell icon for never missing another update. Cheers !
Hello, thanks for viewing our tutorial. It would be helpful if you will provide your email ID to us so that we can send the requested dataset promptly. On the off chance that you need your email ID to be kept hidden from others, we can do that too. Hope that helps.
Hi Shobhan, thanks for checking out our tutorial. Please provide your email ID here in the comment section. Our team will send you the dataset as soon as possible.
Hello Rakesh, thanks for viewing our tutorial. It would be helpful if you will provide your email ID to us so that we could send the requested dataset promptly. On the off chance that you need your email ID to be kept hidden from others, we can do that also. Hope that helps.
Hello Prince, thanks for viewing our tutorial and we hope it is helpful. It would be helpful if you will provide your email ID to us so that we could send the requested dataset promptly.
@@SimplilearnOfficial Please send immediately I would be certainly grateful because I want to run the code in my notebook! Thank you! You lectures are so good. Keep doing better
Hi, thanks for watching our video. We have sent the requested dataset to your mail ID. Do show your love by subscribing to our channel using this link: ruclips.net/user/Simplilearn and don't forget to hit the like button as well. Cheers!
Thank you , but i did not understand the part during exctracting from 2 of legth 3 it tooke only two attribute but not the gender attribute male or fmale ? you answer is highly appreciated
The Gender variable in the dataset is not a significant predictor that can influence the output of the result. Hence, we dropped Gender as an independent variable.
Sir, thank you excellent video to get started. Are the python codes used in this video available to run on Jupyter notebook? Would be of great use for practicing if they are made available.
Hello Endah, thanks for viewing our tutorial. It would be helpful if you will provide your email ID to us so that we could send the requested dataset promptly. On the off chance that you need your email ID to be kept hidden from others, we can do that also. Hope that helps.
Very interesting & clear explanation - Video. I would be interested to have the data set. Grateful if you could share the dataset for each example explained? Thank you Sir. (Youvraj)
Hi Youvraj, thank you for appreciating our work. It would be great if you could share your email ID with us and so we could send the requested dataset easily. If you want your email ID to be kept hidden from others, we can do that as well. Thanks.
Hi Vashist, In scikit-learn library (before v0.18), the train_test_split function was located in the cross_validation module. But know it is located in the model_selection module. If you use "from sklearn.cross_validation import train_test_split", it will show a warning message but will work fine. If you use "from sklearn.model_selection import train_test_split", it will not show any warning messages and does the job of splitting the dataset. You can use any one of them for splitting the dataset into train and test. To upgrade your scikit-learn library to the latest version, you can use: pip install -U scikit-learn or conda update scikit-learn. Hope it helps
I am a beginner, the tutorial is very helpful for me to understand Machine learning. Could you please share the Datasets used for all the algorithms. Thanks a lot in advance.
Hello Rishikesh, thanks for watching our tutorial. It would be helpful if you will provide your email ID to us so that we could send the requested dataset promptly. If you need your email ID to be kept hidden from others, we can do that also. Hope that helps.
Hi Rishikesh, thanks for sending your email ID. We have sent the requested dataset to your mail ID. Do subscribe, like and share to stay connected with us. Cheers :)
It's really a nice session on ml , to do some practice I need the dataset which can use so plz send the dataset on my given id kaushiksatish2341@gmail.com
Hello, thanks for viewing our tutorial. It would be helpful if you will provide your email ID to us so that we can send the requested dataset promptly. On the off chance that you need your email ID to be kept hidden from others, we can do that too. Hope that helps.
You have saved me from months of trouble, you made it so simple to understand and enjoyable thanks for the good work. Please can you send me the code. Thanks
Hello, thanks for viewing our tutorial and we hope it is helpful. It would be helpful if you will provide your email ID to us so that we could send the requested dataset promptly.
Hi, Simplilearn provides online training across the world. We would be happy to help you regarding this. Please visit us at www.simplilearn.com and drop us a query and we will get back to you! Thanks!
Hello, thanks for viewing our tutorial. It would be helpful if you will provide your email ID to us so that we can send the requested dataset promptly. On the off chance that you need your email ID to be kept hidden from others, we can do that too. Hope that helps.
Very well explained in this tutorial ,which is very helpful to learn Machine learning . Could you please share the Data sets used for all the algorithms. Thanks a lot in advance.
Hi Mohana, we are glad that you found our content helpful and informative. We have sent the requested dataset to your mail ID as well. Do subscribe to our channel and get our new video updates directly into your email. If you have any questions related to these videos, you can post in the comments section, we will clear your queries/doubts.
I think RMSE can be find by using "print('RMSE',np.sqrt(metrics.mean_squared_error(y_test,y_pred)))".........but you have mentioned "print('RMSE',np.sqrt(metrics.mean_absolute_error(y_test,y_pred)))" in Linear Regression session. If I use np.sqrt(metrics.mean_squared_error(y_test,y_pred), the result is "4585.4157204675885" which is not efficient! mean_squared_error or mean_absolute_error? Can anyone clarify me?
You can use both Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE) for calculating the efficiency of your model. MAE will always be less than MSE. RMSE is the square root of the average of squared differences between prediction and actual observation. MAE measures the average magnitude of the errors in a set of predictions. Hope this helps!
@@SimplilearnOfficial Basically the RMSE value is 4585 and not 58. Is this value good enough? If not what needs to be done? In the session you too sqrt(MAE) instead of sqrt(MSE).. thats what I need clarification on.
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🔥Purdue - Post Graduate Program in AI and Machine Learning - www.simplilearn.com/pgp-ai-machine-learning-certification-training-course?I7NrVwm3apg&Comments&RUclips
🔥IITG - Professional Certificate Program in Generative AI and Machine Learning (India Only) - www.simplilearn.com/iitg-generative-ai-machine-learning-program?I7NrVwm3apg&Comments&RUclips
🔥Caltech - AI & Machine Learning Bootcamp (US Only) - www.simplilearn.com/ai-machine-learning-bootcamp?I7NrVwm3apg&Comments&RUclips"
this is undoubtedly one of the best, precise and to the point tutorial videos on any learning site! I've tried many videos, but this has by far taught me the most! thanks so much!
WooHoo! We are so happy you love our videos. Please do keep checking back in. We put up new videos every week on all your favorite topics. Whenever you have the time, you must also check out our blog page @simplilearn.com and tell us what you think. Have a good day!
Thanks for watching the video. The link for the dataset used in the video is provided in the description. Thanks!
Thanks for the excellent course. Very easy to understand. Possible to share the python code for me to try out.
Machine Learning is the Future and yours can begin today. Comment below with your email to get our latest Machine Learning Career Guide. Let your journey begin!
mohan.424@gmail.com
Hi, thanks for watching our video. We have sent the requested dataset to your mail ID. Do show your love by subscribing to our channel using this link: ruclips.net/user/Simplilearn and don't forget to hit the like button as well. Cheers!
@@SimplilearnOfficial Thank you very much for the video. Excellently presented! Please send me the salary csv file to niktik7@gmail.com. Thanks once again.
Best Explanation I have ever seen of this topic..!!!!!Can u plzz send me the dataset andother attachments to my mail id as soon as possible..MAIL ID dixit.devraj007@gmail.com
This is a great
tutorial! Could you please send me the study material , datasets and codes used in this tutorial ??
My Email ID :
02pkurle@gmail.com
Very nice! I'm taking a Machine Learning class on Coursrea and after watching this, I understand more of how to implement the algorithms. The class actually got me confused on how to apply it to daily tasks/projects. Now I have some projects in mind. :D
Glad it was helpful! Do show your love by subscribing to our channel using this link: ruclips.net/user/Simplilearn and don't forget to hit the like button as well. Cheers!
Thank you sir for providing such a comprehensive knowledge on ML algorithms. I would like to share that the portion covered in this video is what is asked in most of the data analysis ML interviews. this basics are the building blocks to grow upon.
Thanks for watching our video and sharing your thoughts. Do subscribe to our channel and stay tuned for more. Cheers!
I subscribed your channel for I like your explanation and your response for providing the dataset for each person separately and reading every comment & solving their doubt's.
Thank you for making us a part of your upskilling journey! Learning #CannotBeLockedDown
trust me im leaning ML for almost 6 months and nobody explained as clear as this one. thankzz
Hey Prashanth, thank you for appreciating our work. We are glad to have helped. Do check out our other tutorial videos and subscribe to us to stay connected. Cheers :)
As always, great quality lectures by SimpliLearn. Thank you!
Hello thank you for watching our video .We are glad that we could help you in your learning !
This is a lifesaver. I have learned so much, and it will help me get a ML job.
Keep learning with us .Stay connected with our channel and team :) . Do subscribe the channel for more updates : )
in linear regression python example when visualising test data you used x_train for predict option . i think you should use x_test . can you explain this please?
I really cannot thank you enough, my great appreciation is owed to you.
You're very welcome!
Very easily explained video on machine learning.
Greetings! Thank you for your kind words. Spread the word by liking, sharing and subscribing to our channel! Cheers :).
I love the simplicity of the content and delivery style. Thanks for producing and sharing this.
We are so happy you love our videos. Please do keep checking back in. We put up new videos every day on all your favourite topics Have a good day!
I believe in it one day we have the robots around us,which Can learn and do new opportunities for better solutions for All the part of technological Life.
Yes, we are moving towards that direction already. So let's just sit back and wait for the future filled with Artificial Intelligence!
I am beginner , but able to understand your teaching so well Excellent way of teaching ,Thank you very much
We are so grateful for your kind words. Also, subscribe to our channel and stay tuned for more videos. Cheers!
Good explanation ...Thank you! was wondering, why was random state=0 never touched upon?
PLEASE CHECK: 15:54 RMSE is wrong, you have calculated the square root of Mean absolute error and not MSE
"Hi Keerat,
Thank you for noticing the error. It should have been mean squared error."
this is so good lesson some other only teach the theory no coding but this one show the action of it with plenty of explanation
Excellent explanation by simplilearn...thank you sir..
Thank you for choosing us as your learning partner. We are thrilled to hear that you enjoyed your experience with us! If you are looking to expand your knowledge further, we invite you to explore our other courses in the description box.
Very nicely explained Sir! So Thanks. Regards
You are most welcome
Thanks for this video. It is such a great help for our study
😁
We're thrilled to have been a part of your learning experience, and we hope that you feel confident and prepared to take on new challenges in your field. If you're interested in further expanding your knowledge, check out our course offerings in the description box.
Thank you sir.Your team is doing so good for the purpose of helping students.love & respect for simple learning team
Keep learning with us .Stay connected with our channel and team :) . Do subscribe the channel for more updates : )
Excellent video with great explanation👌👌👌
Hello, thank you for watching our video. We are glad that you liked our video. Do subscribe and stay connected with us. Cheers :)
Beautifully explained, 1 hr well spent.
Glad it was helpful! Thanks for watching!
Very clear explanation of the whole topic with good examples...
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Great video, so much passion and love for the field. Thank you so much.
Thanks for watching! We’re passionate about making machine learning accessible to everyone.
Wonderful video. Thank you so much for creating this. I learnt a lot out of this. 🙏
Glad it was helpful!
at 25:32 it should have been plt.plot(x_test,lr.predict(x_test),color = 'red') right? But x_train is considered.However chart looks almost same.Dont know how.
Hi Mohan!!!
You must be aware our Simple Linear Regression model has been trained on the training set data (lr.fit(X_train, y_train)). We obtained a unique equation which is the simple linear equation for those set of training data points. Since our model is trained on the training set, whether we keep train set or test set data while visualizing the test set results, it won't make any difference. We'll obtain the same regression line.
To learn more on Linear Regression, refer to the following video:
ruclips.net/video/NUXdtN1W1FE/видео.html
amazing summary video,thank for this type of tutorial.
Glad it was helpful!
Really nice work and helpful! Thank You!
Glad it was helpful!
Please correct RMSE formula at 27:55,which is mentioned wrong. Please take care such mistakes
Thank you for bringing this to our attention. We’re sorry you had a bad experience. We’ll strive to do better
Many thanks for putting this top-notch video up. If you could, please share the dataset utilized in the tutorial. :)
Hello, thanks for viewing our tutorial. You can find your requested dataset in the video description. Hope that helps.
Fir linear regression i used abs(error) instead of sqr(error) and worked just fine
That's great. There are always multiple ways to get things done.
Good video. No unnecessary jokes or showoff.
Glad you enjoyed our video! We have a ton more videos like this on ruclips.net/video/ukzFI9rgwfU/видео.html. We hope you will join our community by subscribing to our channel.
A small doubt at 15:36, for RMSE, shouldnt that be a square root of mean squared error instead of mean absolute error?
We are calculating the root mean squared error over passing mean_absolute_error inside np.sqrt function.
Thank you very much for this informative video !
The content and pace is very nice :)
You are welcome!
Very good.always wanted something like this. Plz post more on ML.
Thank you for the appreciation. You can check our videos related to various technologies and subscribe to our channel to stay updated with all the trending technologies.
It was best course explained so far. Can i get the datasets and python codes?
Hello, thanks for viewing our tutorial. You can find your requested dataset in the video description. Hope that helps.
Very nice... wonderful explanation.. thank you
You are most welcome
Great video, Need data sets to practice
Hey Michael, thank you for appreciating our work. We are glad to have helped. Do check out our other tutorial videos and subscribe to us to stay connected. Cheers :)
Thanks for sharing, can you share the example of dataset. Really appreciate it
Hello, thanks for viewing our tutorial. You can find your requested dataset in the video description. Hope that helps.
Informative video 🤙🤙🤙
Hope you enjoyed our video! We have a ton more videos like this on our channel. We hope you will join our community!
Very well explained . Very good video for beginners. I highly recommend . Thank you so much for explaining in detail. The pace is absolutely perfect.
Glad it was helpful!
Dear, this is very impressive class, and thanks for sharing.
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Thank you very much your tutorial is on point.May you share the dataset and the notebooks
Hello, thanks for viewing our tutorial. It would be helpful if you will provide your email ID to us so that we can send the requested dataset promptly. On the off chance that you need your email ID to be kept hidden from others, we can do that too. Hope that helps.
send to godfrey.mbizo@gmail.com
Really knowledgeable.. all algorithms are explained very well..Could you please provide the dataset and python code for these algorithms
Hello, thanks for viewing our tutorial. It would be helpful if you will provide your email ID to us so that we can send the requested dataset promptly. On the off chance that you need your email ID to be kept hidden from others, we can do that too. Hope that helps.
Love learning from you!
Awesome! Thank you!
This video is very informative. Could you please share the data set for each video?
Hello, thanks for viewing our tutorial. You can find your requested dataset in the video description. Hope that helps.
superb.. explanation by mohan sir , Thanks .
Greetings! Thank you for your kind words. Spread the word by liking, sharing and subscribing to our channel! Cheers :). You can also explore our playlists for more Machine Learning - ruclips.net/video/ukzFI9rgwfU/видео.html.
In Decision Tree Explanation what is number and start?
This is an excellent summary of ML. It is spot on with well planned walk through applications and process and how python is used
WooHoo! We are so happy you love our videos. Please do keep checking back in. We put up new videos every week on all your favorite topics. Whenever you have the time, you must also check out our blog page @simplilearn.com and tell us what you think. Have a good day!
Awesome 👍👍👍
Thank you! Cheers!
pure greatness. l enjoyed the video. can you please send me the Logistic Regression dataset for practice
Hello, thanks for viewing our tutorial. You can find your requested dataset in the video description. Hope that helps.
best teaching site
Thanks a ton! Your support makes all the difference 💙
Thank you so much, You mentioned to a very important point for training that I got everything about machine learning. Thanks again!
Hello, thank you for watching our video. We are glad that you liked our video. Do subscribe and stay connected with us. Cheers :)
Can you send me the dataset for more practice? This was a really interesting quick overview of the ML algorithms. Cheers
Hello, thanks for viewing our tutorial. It would be helpful if you will provide your email ID to us so that we can send the requested dataset promptly. On the off chance that you need your email ID to be kept hidden from others, we can do that too. Hope that helps.
Thanks for the straight forward tutorial. Can you please send me the dataset? Thanks
Hello, thanks for viewing our tutorial. You can find your requested dataset in the video description. Hope that helps.
Very useful.. Thank you very much.
We're so glad that you enjoyed your time learning with us! If you're interested in continuing your education and developing new skills, take a look at our course offerings in the description box. We're confident that you'll find something that piques your interest!
Thank you so much for this wonderful online turtorial, I am a beginner to ML and this tutorial are so helpful. May I ask where can I get the data that has been used in this video for practice? Thank UUUU!
Hello, thanks for viewing our tutorial. It would be helpful if you will provide your email ID to us so that we can send the requested dataset promptly. On the off chance that you need your email ID to be kept hidden from others, we can do that too. Hope that helps.
I have a small query in a linear regression where we are first plotting the points of the train data and test data using the linear regression object to verify if both we are testing for both why? we can do it for only testing right as we are calculating the error for only test data
Hi Prasanth, you need to plot the points first for training data and then after you build the model, you need to verify it with test data points. Hope that helps!
I love your sessions. You are one of THE best.
We are glad you found our video helpful, Debanita. Like and share our video with your peers and also do not forget to subscribe to our channel for not missing video updates. We will be coming up with more such videos. Cheers!
Very good explanation... Thank you so much
Hey Majuren, thank you for appreciating our work. We are glad to have helped. Do check out our other tutorial videos and subscribe to us to stay connected. Cheers :)
Very nice explanation of the machine learning. Thank you so much for the tutorial.
Hope you enjoyed our video! We have a ton more videos like this on our channel. We hope you will join our community!
I would be very grateful if I would get each data set of every program tested here in these videos. Thank you.
Hello Jahid, thanks for viewing our tutorial and we hope it is helpful. It would be helpful if you will provide your email ID to us so that we could send the requested dataset promptly.
Awesome Mohan!
Hi Mukesh, we appreciate the kind comment! enjoy!
Very nice lecture with good example. Thank you Simplilearn. By the way I have got my PMI Risk Management Certification through you. Can you please send me the ML algorithms? Thank you again
Hello, thanks for viewing our tutorial. You can find your requested dataset in the video description. Hope that helps.
Thank you Simplilearn for the video. Please share the data sets used for projects.
Hello Nik, thanks for viewing our tutorial and we hope it is helpful. It would be helpful if you will provide your email ID to us so that we could send the requested dataset promptly.
I think you may have a typo in step 9, when calculating the RMSE you use sqrt of AME in the code.
Thanks for the correction. We will share the feedback to the relevant team.
Nice explaination ...thnx
Most welcome
Very good explanation
Thanks and welcome
Clear explanation!
Great that you liked the tutorial, Krzyazlof! If you agree that Machine Learning is good career move, Please refer to this, www.simplilearn.com/big-data-and-analytics/machine-learning-certification-training-course.. Also, Subscribe to our channel by clicking on the bell icon for never missing another update. Cheers !
This is fantastic!!!!
Hello thank you for watching our video .We are glad that we could help you in your learning !
Very nice explanation..Plz share the dataset
Hello, thanks for viewing our tutorial. It would be helpful if you will provide your email ID to us so that we can send the requested dataset promptly. On the off chance that you need your email ID to be kept hidden from others, we can do that too. Hope that helps.
For me, as a beginner, the tutorial is very helpful. Could you please share the Datasets used for all the algorithms. Thanks a lot in advance.
Hi Shobhan, thanks for checking out our tutorial. Please provide your email ID here in the comment section. Our team will send you the dataset as soon as possible.
Sir, Your lecture on machine learning is very nice and for depth knowledge on this topics please send the salary data set.
Hello Rakesh, thanks for viewing our tutorial. It would be helpful if you will provide your email ID to us so that we could send the requested dataset promptly. On the off chance that you need your email ID to be kept hidden from others, we can do that also. Hope that helps.
...but how can I get the code(dataset) am trying to download it's saying it's not available in my country: Zimbabwe
Hello Prince, thanks for viewing our tutorial and we hope it is helpful. It would be helpful if you will provide your email ID to us so that we could send the requested dataset promptly.
@@SimplilearnOfficial Please send immediately I would be certainly grateful because I want to run the code in my notebook! Thank you! You lectures are so good. Keep doing better
@@SimplilearnOfficial send at: aprincey86@gmail.com
Hi, thanks for watching our video. We have sent the requested dataset to your mail ID. Do show your love by subscribing to our channel using this link: ruclips.net/user/Simplilearn and don't forget to hit the like button as well. Cheers!
@@SimplilearnOfficial Thank you! Got 'em! I'm a subscriber already
Thank you , but i did not understand the part during exctracting from 2 of legth 3 it tooke only two attribute but not the gender attribute male or fmale ? you answer is highly appreciated
The Gender variable in the dataset is not a significant predictor that can influence the output of the result. Hence, we dropped Gender as an independent variable.
Amazing Content ....
Thanks 🙂
excellent presentation
Thank you! Cheers!
Sir, thank you excellent video to get started. Are the python codes used in this video available to run on Jupyter notebook? Would be of great use for practicing if they are made available.
following
Hello, thanks for viewing our tutorial. You can find your requested dataset in the video description. Hope that helps.
help please in linear regression i have been following same steps and rule but i am getting different values. I am new to it and unable to resolve it
A very good explanation of Machine Learning Algorithms. Can you send the dataset. Thanks.
Hello Endah, thanks for viewing our tutorial. It would be helpful if you will provide your email ID to us so that we could send the requested dataset promptly. On the off chance that you need your email ID to be kept hidden from others, we can do that also. Hope that helps.
Hello , this is an wonderful video. Can I have the PPT / PDF shown in this course? We can study then offline also. TY
Very interesting & clear explanation - Video. I would be interested to have the data set. Grateful if you could share the dataset for each example explained? Thank you Sir. (Youvraj)
Hi Youvraj, thank you for appreciating our work. It would be great if you could share your email ID with us and so we could send the requested dataset easily. If you want your email ID to be kept hidden from others, we can do that as well. Thanks.
18:35 why are you putting -1 in iloc ?
-1 is used to exclude in last column that is the target column.
i have exam in an hour and am here now :O :)
All the best! And hope this helps!
why in logistic regression you used 'sklearn.cross_validation' in spliting the dataset and 'sklearn.model_selection' in other algorithm
Hi Vashist,
In scikit-learn library (before v0.18), the train_test_split function was located in the cross_validation module. But know it is located in the model_selection module.
If you use "from sklearn.cross_validation import train_test_split", it will show a warning message but will work fine.
If you use "from sklearn.model_selection import train_test_split", it will not show any warning messages and does the job of splitting the dataset.
You can use any one of them for splitting the dataset into train and test.
To upgrade your scikit-learn library to the latest version, you can use:
pip install -U scikit-learn
or
conda update scikit-learn.
Hope it helps
@@SimplilearnOfficial Hi! could I get the data too? rat.qualco@gmail.com
I am a beginner, the tutorial is very helpful for me to understand Machine learning. Could you please share the Datasets used for all the algorithms. Thanks a lot in advance.
Hello Rishikesh, thanks for watching our tutorial. It would be helpful if you will provide your email ID to us so that we could send the requested dataset promptly. If you need your email ID to be kept hidden from others, we can do that also. Hope that helps.
@@SimplilearnOfficial Sure, My email id is rishikesht6@gmail.com. Thanks a lot.
Hi Rishikesh, thanks for sending your email ID. We have sent the requested dataset to your mail ID. Do subscribe, like and share to stay connected with us. Cheers :)
It's really a nice session on ml , to do some practice I need the dataset which can use so plz send the dataset on my given id
kaushiksatish2341@gmail.com
Hi, thanks for the kind comment. We have sent the requested dataset to your mail ID. Do subscribe, like and share to stay connected with us. Cheers :)
Can you send the data set ... employee salary example
Hello, thanks for viewing our tutorial. It would be helpful if you will provide your email ID to us so that we can send the requested dataset promptly. On the off chance that you need your email ID to be kept hidden from others, we can do that too. Hope that helps.
You have saved me from months of trouble, you made it so simple to understand and enjoyable thanks for the good work. Please can you send me the code. Thanks
Hello, thanks for viewing our tutorial and we hope it is helpful. It would be helpful if you will provide your email ID to us so that we could send the requested dataset promptly.
@@SimplilearnOfficial olaoluwa38@gmail.com, Thanks
i need the code of 29:10 - 52:49 Logistic regression
Hello, thanks for viewing our tutorial. You can find your requested dataset in the video description. Hope that helps.
very good explanation.thank you very much.
Well explained!
Great explanations, thank you.
Hi .do you have the continuation of this topic of ML for unsupervised algorithms ?
Hi, Simplilearn provides online training across the world. We would be happy to help you regarding this. Please visit us at www.simplilearn.com and drop us a query and we will get back to you! Thanks!
I want dataset from where I get this??
Hello, thanks for viewing our tutorial. It would be helpful if you will provide your email ID to us so that we can send the requested dataset promptly. On the off chance that you need your email ID to be kept hidden from others, we can do that too. Hope that helps.
Very well explained in this tutorial ,which is very helpful to learn Machine learning . Could you please share the Data sets used for all the algorithms. Thanks a lot in advance.
could you please send all datasets which was explained in this tutorial mohanadurga54@gmail.com
Hi Mohana, we are glad that you found our content helpful and informative. We have sent the requested dataset to your mail ID as well. Do subscribe to our channel and get our new video updates directly into your email. If you have any questions related to these videos, you can post in the comments section, we will clear your queries/doubts.
I think RMSE can be find by using "print('RMSE',np.sqrt(metrics.mean_squared_error(y_test,y_pred)))".........but you have mentioned "print('RMSE',np.sqrt(metrics.mean_absolute_error(y_test,y_pred)))" in Linear Regression session.
If I use np.sqrt(metrics.mean_squared_error(y_test,y_pred), the result is "4585.4157204675885" which is not efficient!
mean_squared_error or mean_absolute_error?
Can anyone clarify me?
You can use both Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE) for calculating the efficiency of your model.
MAE will always be less than MSE. RMSE is the square root of the average of squared differences between prediction and actual observation. MAE measures the average magnitude of the errors in a set of predictions. Hope this helps!
@@SimplilearnOfficial Basically the RMSE value is 4585 and not 58. Is this value good enough? If not what needs to be done?
In the session you too sqrt(MAE) instead of sqrt(MSE).. thats what I need clarification on.
Clear explaination..
Hi Tiada, we appreciate the kind comment! enjoy!