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Do you have any questions on this topic? Please share your feedback in the comment section below and we'll have our experts answer it for you. Also, if you would like to have the dataset for implementing the use case shown in the video, please comment below and we will get back to you. Thanks watching the video. Cheers !!
Hello Georgy, thanks for the kind comment. 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.
Beautifully explained the whole sklearn methods. I have been watching youtube videos to learn this topic for a while, nonetheless I couldn't get the juice until now. I suppose this video is 100% effective for those who wants to get straight to the point.
Hey Mahyar, 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 :)
Hey, 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 :)
wow....your tutorial was just bullz eye.Right on spot what was needed.A big thumbs up fir what was needed about get going about scikit learn.Keep it up!
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!
Hey, thanks for your great tutorial! But i have one Question about the StandardScaler Function: When you scale the trainingset, don't you have to scale the testset (and the data you're using in the later Application) with the same Values? As an Example: The Feature A has a Mean of 2 and a Std of 0.3, so you have to normalize the testset with these Values (because you have to pretend the Testset is "unknown"). So how can i extract the Mean and Std Values?
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!
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.
Glad you enjoyed our video! We are sorry to say that this tutorial doesn't have the second part. And also don't forget to support us by subscribing to our channel. Cheers!
Hi, you made the transform of the X_train and X_test separately. Would not it be a better idea to rescale when they are together and then separate them?
As Christopher also added, you prefer to do the transformation separately since we wanna get the main features just from our training data (mean & variance ) and then use those features to transform also the testing data, else there is the risk of overfitting
Thanks, very helpful tutorial. I just have one question, why the precision value in the classification report is not equal to the accuracy in the confusion matrix?
Hey Mariav, 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 :)
Great video concise, direct to the point, hands-on makes one wanted to study and play at the same time with Machine Learning and then go deeper. Just found this much better approach than traditional Excel and legacy SAS JMP. No cut and paste for a disciplined developer - learn as you type! I have a use case for agricultural work I can apply the lessons here thanks! Please send me a link to the practice dataset and Jupyter Notebook file (to make is a reference solution set versus my version of code).
Thanks for the video! How would I go about taking my model and exporting it so that I can use it in my own different applications? Like, how do I find the actual code of the model that I can copy into another application to use regularly? Also, when refitting with new training data, does the standard scalar remember the scale to which it scaled the old data and apply that to the new data?
Been following this tutorial to the letter with an exception of the dataset(im using a set with 4500 lines ) When i get to 28:28 in the video i get the following error object of type 'CategoricalDtype' has no len() does any one here have a ide of why?
I have been having trouble downloading the dataset, and some others from Simplilearn videos. It downloads as .html file. Someone help me out. How do yo download the datasets?
Wow, this is a masterful crash course for people that alr has some knowledge, learnt quite a few things as well, thanks so much!! Also, are there any plans for more episodes of scikit learn?
Hello, thank you for the amazing feedback. We are glad to have helped. We do not have any current plan in making more videos about SciKit. However, we will be coming up with advanced videos for each topics soon. So, do check out our other tutorial videos and subscribe to us to stay connected. Cheers :)
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!
@@SimplilearnOfficial yes and no. More I wish you will send me here link with algorithms description that I can't find on your site now it's shown on 38:36 min
Hello Halyna, 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.
This video is for beginners and Intermediate level. For more advance concepts, you can check out our machine learning course: www.simplilearn.com/big-data-and-analytics/machine-learning-certification-training-course
Hello. I am trying to sort thru a data set with values either 0 or 1 and separate them into 2 bins but the bin declaration bins=(2,.5,1) is giving me a value error. how would I store all of that data in 2 bins?
Hi Sebastian, we are glad you found our video informative. It would be helpful if you will provide your email ID to us so that we could send the requested dataset promptly.
Thanks for sharing the tutorial. Taught in a very lucid way. Quick question if we write thebelow code snippet bins=(2,6.5,8) group_names=['0','1'] wine['quality']=pd.cut(wine['quality'],bins=bins,labels=group_names) It will transform the quality column into binary values without further encoder and transform_fit. Then we do not need to do LabelEncoder() and label_quality.fit_transform(wine['quality']) . Am I correct?
Hey Russa, 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.
@@SimplilearnOfficial I actually had a dataset that I am working with but I am wondering if you could help guide me on how to do ML for it so I can predict.
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, Thanks for providing a great intro to scikit learn.. Im trying to recreate the analysis on a test file, but im running into an issue. I am trying to predict the font colour for a coloured background in an excel file.. I created a bunch of random RGB values and found their grayscale value to determine if the font colour should be black or white. The black or white determination is recorded in a 4th column (after R,G,B), as 0 or 1. At cell 7 of runtime I get a KeyError - Traceback to the name of the 4th column, 'bgval'.. I've ensured everything is spelled correctly, i tried updating the CSV file to make sure the name does not confuse pandas somehow.. I edited on github instead of the csv file directly, but it reads properly with the prior cells, showing updated values. Is it because I have a binary test column? The bins are labeled (0,0.5,1), so I thought that should separate the bins to mimic the tutorial 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.
Bins work in intervals. So one bin for values between 2-6.5 and another for values between 6.5-8. If you only put bins(2,6.5) you will only get one bin for range 2-6.5
Could it be possible that the random forest mislabels a lot of good wines because the training data is imbalanced and has a lot more bad than good wines?
I didn't understand why you use fit_transform on X_train but only transform on X_test. Shouldn't you also fit for the testing since it's how it's being trained?
fitting data means you want the algorithm to learn from it. For that purpose, we use the training data set. But the problem is a model could do very well on the training data to make predictions but it doesn't perform well when faced with unseen data that the model never seen before. We don't care too much about how the data performed well on the training set, we want our model to do well on the unseen data. The test set is used as a proxy for unseen data. If we fit the model on the test set, it means the algorithm is going to learn from it, which we don't want in the initial step of model building. We want to use the test set after we were going through all the process. We want to use the test set at last to see how good our model do or generalize in the real world. That is why he only used the fitting and transforming on the training data but not on the test data. I hope this helps.
Thanks for an excellent tutorial. I found the data set online and used Jupyter to successfully replicate it with one exception. The neural network example did not converge. How can I submit my notebook privately?
Hi Gaurie. I'm starting to learn machine learning/scikit. Thanks for your tutorial. Please send me the dataset and code. Appreciate ...you are a gem of an instructor....
Hi Gauransh, thanks for watching our video. We have sent the requested dataset to your mail ID. 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.
Hello Kaushik, 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.
Hello, 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 Steve, 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 Gustavo, it is possible to predict the prices of the wine using the wine dataset. Since, price is a quantitative variable, you need to use Linear Regression model.
I am new in machine learning and now I am facing an issue. I have 7 projects I would like to predict whether a pull request would be rejected or not (Yes or No). And I would like to build a prediction model by using data from 6 projects as source project and predict the rejection of the pull request in the seventh project as a target project. Can you please tell me how can I structure my algorithm in Scikit-learn? Hope that my question is clear. Thanks
First, you need to ensure your data is in the right format. One problem you might face when pulling data from different sources is the structure. gather all the information into a single sheet and then you can proceed as usual.
Hi, I get ModuleNotFoundError for some of the sklearn imports in Jupyter. I have everyting needed isntalled. Do you have a guess as to what the problem could be?
Daaang, I know this is 2 years old, but "restart and run all" for the kernel didn't work at the very beginning so my entire Jupyter notebook was erroring out :(
"Hi Inee, Restart and run all option in Jupyter notebook restarts the kernel and run all the cells. It will throw errors if any of coding cells have an error."
Hello Sandy, 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.
Hi Sandy, thanks for watching our video. We have sent the requested dataset to your mail ID. Do check out our other tutorial videos and subscribe to us to stay connected. Cheers :)
Hello Shaista, 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, 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, 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: th-cam.com/users/Simplilearn and don't forget to hit the like button as well. Cheers!
Hello, 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.
In machine learning, support-vector machines (SVMs, also support-vector networks) are supervised learning models with associated learning algorithms that analyze data used for classification and regression analysis.
Hello Triyug, 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.
Hello Oliver, 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.
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Do you have any questions on this topic? Please share your feedback in the comment section below and we'll have our experts answer it for you. Also, if you would like to have the dataset for implementing the use case shown in the video, please comment below and we will get back to you. Thanks watching the video. Cheers !!
File "", line 3
from sklearn.model_selection import train_test_split
^
SyntaxError: invalid syntax
Where is a mistake?
Fantastic video man. Any chances we can get our hands on the file that you worked on? Maybe through you Git profile?
Hello Georgy, thanks for the kind comment. 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.
@@georgyachkouty3127 archive.ics.uci.edu/ml/machine-learning-databases/wine-quality/
Hi! Please send me the dataset and the Python script. juan_neufeld@hotmail.com Thank you!
Beautifully explained the whole sklearn methods. I have been watching youtube videos to learn this topic for a while, nonetheless I couldn't get the juice until now. I suppose this video is 100% effective for those who wants to get straight to the point.
Hey Mahyar, 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 :)
May you have an eternal bliss for the effort you put in doing things in the world, my friend!
Hey, 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 :)
wow....your tutorial was just bullz eye.Right on spot what was needed.A big thumbs up fir what was needed about get going about scikit learn.Keep it up!
Hey Muhammad, thank you for watching our video. We are glad that you liked our video. Do subscribe and stay connected with us. Cheers :)
This is the best tutorial ever about his topic. All the information is given so clear. Thank you very much and do more!!!
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!
Hey, thanks for your great tutorial! But i have one Question about the StandardScaler Function: When you scale the trainingset, don't you have to scale the testset (and the data you're using in the later Application) with the same Values? As an Example: The Feature A has a Mean of 2 and a Std of 0.3, so you have to normalize the testset with these Values (because you have to pretend the Testset is "unknown"). So how can i extract the Mean and Std Values?
this is tutorial is incredible and very helpful. i had many doubts about scikit-learning ,now with this tutorial my problems have been solved
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Thank you!!! super straightforward and easy to follow along.
Glad it was helpful!
Great tutorial. Thanks!
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!
Great Tutorial! Well Done!
Hope you enjoyed our video! We have a ton more videos like this on our channel. We hope you will join our community!
Great video!!
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.
Thanks for this incredible tutorial, Does it have a second part?
Glad you enjoyed our video! We are sorry to say that this tutorial doesn't have the second part. And also don't forget to support us by subscribing to our channel. Cheers!
Many thanks for the wonderful tutorial
Glad it was helpful!
Hi, you made the transform of the X_train and X_test separately. Would not it be a better idea to rescale when they are together and then separate them?
Yes that could be done too.
If you scale them together then you risk data leakage. This is not typically advised.
As Christopher also added, you prefer to do the transformation separately since we wanna get the main features just from our training data (mean & variance ) and then use those features to transform also the testing data, else there is the risk of overfitting
Thanks, very helpful tutorial. I just have one question, why the precision value in the classification report is not equal to the accuracy in the confusion matrix?
Nice video, thank you.
Glad you liked it!
is this the best version of this video? sound quality is really low
Thank you so much for bringing this to our attention. We reported this right away to the relevant department.
Sound is okay. Perhaps check elsewhere.
An excellent video indeed! Had a doubt; why don't we use fit_transform for the x_test data?
Amazing!
much appreciated.
You're welcome!
Very useful, thank you so much! Great lesson!
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Thanks for this excellent video!
Hey Mariav, 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 :)
Sir. You nailed it...
Thanks for the compliment. Do subscribe to our channel and stay tuned for more.
Great job, thank you.
Our pleasure!
Great video concise, direct to the point, hands-on makes one wanted to study and play at the same time with Machine Learning and then go deeper. Just found this much better approach than traditional Excel and legacy SAS JMP. No cut and paste for a disciplined developer - learn as you type! I have a use case for agricultural work I can apply the lessons here thanks! Please send me a link to the practice dataset and Jupyter Notebook file (to make is a reference solution set versus my version of code).
Glad it was helpful! It would be helpful if you will provide your email ID to us so that we could send the requested dataset promptly.
berns.buenaobra@gmail.com
One of the best learning videos...can you please add the wine data file in google drive
Hello, thanks for viewing our tutorial. You can find your requested dataset in the video description. Hope that helps.
Thanks for the video! How would I go about taking my model and exporting it so that I can use it in my own different applications? Like, how do I find the actual code of the model that I can copy into another application to use regularly?
Also, when refitting with new training data, does the standard scalar remember the scale to which it scaled the old data and apply that to the new data?
Been following this tutorial to the letter with an exception of the dataset(im using a set with 4500 lines )
When i get to 28:28 in the video i get the following error
object of type 'CategoricalDtype' has no len()
does any one here have a ide of why?
Hi Julian, len() does not work on datasets.
Thanks for this straightforward tutorial!😊
Glad it was helpful!
I have been having trouble downloading the dataset, and some others from Simplilearn videos. It downloads as .html file. Someone help me out. How do yo download the datasets?
Hello, thanks for viewing our tutorial. You can find your requested dataset in the video description. Hope that helps.
Thanks for the video!
Hey, thank you for watching our video. We are glad that you liked our video. Do subscribe and stay connected with us. Cheers :)
@@SimplilearnOfficial You are welcome!
Great tutorial!👍,how can we get the dataset!?below is my mail id
vcdwbi@gmail.com
great explanation bruh
Glad you think so!
Wow, this is a masterful crash course for people that alr has some knowledge, learnt quite a few things as well, thanks so much!!
Also, are there any plans for more episodes of scikit learn?
Hello, thank you for the amazing feedback. We are glad to have helped. We do not have any current plan in making more videos about SciKit. However, we will be coming up with advanced videos for each topics soon. So, do check out our other tutorial videos and subscribe to us to stay connected. Cheers :)
@@SimplilearnOfficial Looking fwd to that, subscribed!
Thanks for joining our community. We welcome you!
You are amazing, very well explained.
Hello, thank you for watching our video. We are glad that you liked our video. Do subscribe and stay connected with us. Cheers :)
Great tutorial, thank you very much!
You're very welcome!
Very useful, thank you so much. I had only one issue. my dataset has a lot of categorical data wasn't sure how to convert it
The common practice is to create a numerical column and assinging a determined value depending on the category.
very useful video.thanks
Very welcome! Do subscribe to our channel and stay tuned for more.
Thx for explaining :)
But how could I predict the former raiting and not only if the wine is good or bad?
How to access the CSV file which you are using in the tutorial?
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!
Why distill quality down to just "good" or "bad"? How can we rework the example to predict the numerical value for quality?
thank you so much, it's really helpful !
Greetings! Thank you for your kind words. Spread the word by liking, sharing and subscribing to our channel! Cheers :).
can you explain why you dont use sc.fit_transform on line 5?great video.
Here is the dataset 'winequality-red.csv' github.com/zygmuntz/wine-quality/blob/master/winequality/winequality-red.csv
Thanks for that!
Link to datasets:
archive.ics.uci.edu/ml/machine-learning-databases/wine-quality/
Note that these are semicolon delimited
Thanks for sharing the dataset link.
I would apply the scaler to the features before splitting the samples to training and testing sets.
Keep learning with us .Stay connected with our channel and team :) . Do subscribe the channel for more updates : )
Very useful, love it
Hi Ethamane, we appreciate the kind comment! enjoy!
Thank you for this great tutorial
You're very welcome!
Thanks for video! Please share link on 38:36
Hi Halyna, are you looking for the dataset?
@@SimplilearnOfficial yes and no. More I wish you will send me here link with algorithms description that I can't find on your site now it's shown on 38:36 min
Hello Halyna, 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. Kindly upload tutorial for image dataset with svm
Thanks for your suggestion. We will look into it. Thanks.
Loved the course. On a scale of beginner, intermediate and advance. What would you say about your course??
This video is for beginners and Intermediate level. For more advance concepts, you can check out our machine learning course: www.simplilearn.com/big-data-and-analytics/machine-learning-certification-training-course
Hello. I am trying to sort thru a data set with values either 0 or 1 and separate them into 2 bins but the bin declaration bins=(2,.5,1) is giving me a value error. how would I store all of that data in 2 bins?
I have just started with the tutorial and it seems very informative. I would like to have the dataset.
Hi Sebastian, we are glad you found our video informative. It would be helpful if you will provide your email ID to us so that we could send the requested dataset promptly.
great tutorial thanks
Its our pleasure!
How to get the parameters for the prediction, so that we could use that parameters for future estimate offline in some other software like Excel?
Thanks for sharing the tutorial. Taught in a very lucid way.
Quick question
if we write thebelow code snippet
bins=(2,6.5,8)
group_names=['0','1']
wine['quality']=pd.cut(wine['quality'],bins=bins,labels=group_names)
It will transform the quality column into binary values without further encoder and transform_fit.
Then we do not need to do LabelEncoder() and label_quality.fit_transform(wine['quality']) .
Am I correct?
Hey Russa, 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 :)
How can I do sklearn for a csv with multiple values.
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.
@@SimplilearnOfficial I actually had a dataset that I am working with but I am wondering if you could help guide me on how to do ML for it so I can predict.
Where can I find the data set?
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.
@@SimplilearnOfficial kompajam@gmail.com
I have a doubt
Why not predict y_test?
Explain(classification_report(y_test, pred_rfc)
Hi, Thanks for providing a great intro to scikit learn.. Im trying to recreate the analysis on a test file, but im running into an issue. I am trying to predict the font colour for a coloured background in an excel file.. I created a bunch of random RGB values and found their grayscale value to determine if the font colour should be black or white. The black or white determination is recorded in a 4th column (after R,G,B), as 0 or 1. At cell 7 of runtime I get a KeyError - Traceback to the name of the 4th column, 'bgval'.. I've ensured everything is spelled correctly, i tried updating the CSV file to make sure the name does not confuse pandas somehow.. I edited on github instead of the csv file directly, but it reads properly with the prior cells, showing updated values. Is it because I have a binary test column? The bins are labeled (0,0.5,1), so I thought that should separate the bins to mimic the tutorial example.
Thank you so much @simplilearn,incredible tutorial and explanation!!would be even better if you could provide Jupytr notebook link
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.
In bins(2,6.5,8)
What is use of 8?
Bins work in intervals. So one bin for values between 2-6.5 and another for values between 6.5-8. If you only put bins(2,6.5) you will only get one bin for range 2-6.5
Thanks for your input!
thanks so helpful
Very welcome!
If I put directly bins(2,8) then??
Love it 😊
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Could it be possible that the random forest mislabels a lot of good wines because the training data is imbalanced and has a lot more bad than good wines?
"Hi Lawliet,
Yes, it is definitely possible that the predictions might completely go wrong if the data is inaccurate or has a lot of noise."
Shouldn't the data we feed into our model for prediction (X new) be an numpy array? Thanks
sklearn algorithms can be fed using numpy arrays or pandas dataframes, arrays as input are not an obligation
Hi Daniel, it could be either an array or data frame. Both work fine.
hi jst a review, the bckground voice is unsuitable in any of the earphones. please check it out
We are sorry about that, we will share the feedback with the relevant department
Excellent video! Pretty straight forward, you just need to have a little background on Python to understand the code
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I didn't understand why you use fit_transform on X_train but only transform on X_test. Shouldn't you also fit for the testing since it's how it's being trained?
fitting data means you want the algorithm to learn from it. For that purpose, we use the training data set. But the problem is a model could do very well on the training data to make predictions but it doesn't perform well when faced with unseen data that the model never seen before. We don't care too much about how the data performed well on the training set, we want our model to do well on the unseen data. The test set is used as a proxy for unseen data. If we fit the model on the test set, it means the algorithm is going to learn from it, which we don't want in the initial step of model building. We want to use the test set after we were going through all the process. We want to use the test set at last to see how good our model do or generalize in the real world. That is why he only used the fitting and transforming on the training data but not on the test data. I hope this helps.
Thanks for your valuable input!
Where can we access the dataset you used onthis tutorial
i can't access the dataset only the notebook
Hello, thanks for viewing our tutorial. You can find your requested dataset in the video description. Hope that helps.
Thanks for an excellent tutorial. I found the data set online and used Jupyter to successfully replicate it with one exception. The neural network example did not converge. How can I submit my notebook privately?
Hi Perry, you can share the query to this email ID: kennet.rajan@simplilearn.net
We will try to help you out. Thanks.
Hi Gaurie. I'm starting to learn machine learning/scikit. Thanks for your tutorial. Please send me the dataset and code. Appreciate ...you are a gem of an instructor....
gaurtcd@gmail.com
Hi Gauransh, thanks for watching our video. We have sent the requested dataset to your mail ID. 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.
Can I get that data set?
Hello Kaushik, 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.
@simplilearn you are really awesome man !! Such a great work
May I know from where the data sets can be taken ??
Hello, 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.
This Dataset is from UC Irvine . Link : archive.ics.uci.edu/ml/datasets/wine+quality
I need the datasets used in this video please.
Hello, thanks for viewing our tutorial. You can find your requested dataset in the video description. Hope that helps.
Hi, very well done. Could you please me the dataset used in this video. Thanks again
Hello Steve, 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, where i can get that data?
Hello, thanks for viewing our tutorial. You can find your requested dataset in the video description. Hope that helps.
Hi, I' m new at jupyter editor and with Scikit-Learn, I was wondering if u could help me out with some issues like reading the csv file
Hi, you can check out our Jupyter notebook video to learn interface of it: th-cam.com/video/3C9E2yPBw7s/w-d-xo.html
Could I use this model to predict wine prices? I mean, I would not use the bins, would like to get an estimation of the price. btw awesome video
Hi Gustavo, it is possible to predict the prices of the wine using the wine dataset. Since, price is a quantitative variable, you need to use Linear Regression model.
I am new in machine learning and now I am facing an issue. I have 7 projects I would like to predict whether a pull request would be rejected or not (Yes or No). And I would like to build a prediction model by using data from 6 projects as source project and predict the rejection of the pull request in the seventh project as a target project. Can you please tell me how can I structure my algorithm in Scikit-learn? Hope that my question is clear.
Thanks
First, you need to ensure your data is in the right format. One problem you might face when pulling data from different sources is the structure. gather all the information into a single sheet and then you can proceed as usual.
Hi,
I get ModuleNotFoundError for some of the sklearn imports in Jupyter. I have everyting needed isntalled. Do you have a guess as to what the problem could be?
Got it fixed!
Great video!
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Great tutorial! Where could I get the video?
Thanks for the kind comment. You can get our videos through our TH-cam channel. Thanks.
I have a doubt... I don't understand the purpose of X and y variables for separating the data set
"Hi Ezhil,
In scikit learn, we use X and y for dividing the data between training and testing set."
Daaang, I know this is 2 years old, but "restart and run all" for the kernel didn't work at the very beginning so my entire Jupyter notebook was erroring out :(
"Hi Inee,
Restart and run all option in Jupyter notebook restarts the kernel and run all the cells. It will throw errors if any of coding cells have an error."
why didn't we scaled Y_train data please reply ?
what if we have more than one qualities.. such as qualities range from 1 to 10. in this case, how code will change?
Sure, could you please share your mail ID to get the dataset? THanks.
@@SimplilearnOfficial kindly, give me the edited code for more than two qualities as well.
ahsannaseer1122@gmail.com
Please tell me which library and tools should i use to make a chatbot
Use the NLTK package to build chatbots. Stick around as we have a tutorial on the same coming up soon.
I AM getting an error 'something like 'keyerror':quality
could you help to solve this?
what are the prerequisites for this video ?
Hi Aditya, we suggest you to learn scikit after having some knowledge of python, Numpy and Pandas. Thanks.
Great Tutorial!
Please send me the datasets used in this video..
Hello Sandy, 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.
@@SimplilearnOfficial sandy.momo21@gmail.com
Please keep it hidden, Thanks!
Hi Sandy, thanks for watching our video. We have sent the requested dataset to your mail ID. Do check out our other tutorial videos and subscribe to us to stay connected. Cheers :)
Simplilearn can I get the dataset too
awesomebaron007@gmail.com
@@SimplilearnOfficial can u send me dataset: nvnhat.17ck1@gmail.com
Sir, What is bins (in preprocessing zone)?
v.good work
sir r u send me this source code Scikit-Learn Tutorial | Machine Learning With Scikit-Learn | Sklearn | Python Tutorial | Simplilearn
Hello Shaista, 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.
Great tutorial. Thanks. Would like to have data and code
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 nice tutorial! please how to I access the datasets i really need them...
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: th-cam.com/users/Simplilearn and don't forget to hit the like button as well. Cheers!
Can i plz get this wine dataset....Thanking u in anticipation
Hello, 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.
The dataset is at the UCI Machine Learning Repo. You will need to do some work to get this dataset properly ready for preprocessing.
why do i keep getting ranked numbers after label encoding my data
i think svm refer to support vector machine not support vector modal...
In machine learning, support-vector machines (SVMs, also support-vector networks) are supervised learning models with associated learning algorithms that analyze data used for classification and regression analysis.
can you provide the wine data set which you have used on your program
Hello Triyug, 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.
was best bro ___
Thank you! Do subscribe to our channel and stay tuned.
Hi, I was wondering if I could get access to the dataset please?
Hello Oliver, 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.
Can you do a tutorial showing the Linear Algebra/Calculus required for both machine learning and deep learning? Great video btw
Hey Harjit, thank you for watching our video. We will definitely look into your suggestions. Do subscribe and stay tuned for updates on our channel. Cheers :)