Great explanation. I was shocked to know that this is the only video he put up in this channel... i really liked this video and patiently listened to it. I have subscribed this channel in the hope that one day you will continue. Thank you for creating this video
Hello. Thanks for your video. it was really great. I have one question though. does this line mean that only first 200 rows that their class value is 2 will be plotted? I mean we will see only 200 points in the plot? benign_df = cell_df[cell_df['class'] == 2] [0:200]
superb Sir. Well Explained. I have faced issue at last. when I code classifier.fit(x_train , y_train) . given error has occurred. ValueError: could not convert string to float: '?' . could you kindly help me out
i think u have to first draw a pair plot then u have to see for the best gausian and according to that u have to apply svm for each good gausian attributes, so u will find out what is best influencing
My dataset has no numeric value.its a news archive dataset and i want to detect the noveltyfrom this news archive.i want to use SVM.I need a help.Can anyone help me please?
refer to point 6 of the video.u can convert datatype of each and every column.else u can manually convert those non numeric values in the xlsx file. say if u have attribute color{red,blue,green} then u can change them to color{1,2,3}
Hi @Anmol, a hyperplane in a 2D plot, would be a simple line (or curve) that can separate the different available classes in the data sets. I will try posting a new video, but meanwhile you can refer this nice blog - chrisalbon.com/machine_learning/support_vector_machines/plot_support_vector_classifier_hyperplane/
best ever video on youtube on SVM.
It's been almost two years now and you're still helping people with this video. Thank you!!
*four years
Great explanation. I was shocked to know that this is the only video he put up in this channel... i really liked this video and patiently listened to it. I have subscribed this channel in the hope that one day you will continue.
Thank you for creating this video
Thankyou for your Explanation, I went through a lot of videos in youtube about python, but no one told about Help function.
Best ever video on RUclips on SVM❣
The better video ever clarifying SVM!!😃
Best video to explain SVM to a beginner!
This video helping me to finish my essay and got bachelor title. Thx.
really very informative video on svm
Thank you for making the best lecture about SVM❤
Very thorough explanation, Thank You!
Thank you for great explanation Sir, it helped a lot learning practical implementation of SVM
Very comprehensive, detailed and well-elaborated video on SVM, The top best videos on SVM on RUclips. Thanks for your effort and teaching...
Its such a great video on SVM that I had understood it from depth we want more such videos please...
Best video for intro to SVM!
Thank u so much sir i have no words to explain my gratitude for this video
great work sir . we also need a video for chatbot also
That's a very precise and best explanation I have come across.Excellent
Best video on svm.good explained
keep going ,the session was very good!
Thank you - extremely helpful.
Thank you so much for sharing your knowledge, It was really helpful, keep doing the good work
Beautifully explained. Thank you!
Awsome explanation..... Thank you sir.......will you make something on random forest, dtree, ann, naive bays, kmeans
this guy is amazing i swear
Very informative and clear lecture 👍🏻👍🏻
Awesome explanation. Cleared all my doubts. Could you please share the code/ jupyter notebook in the comment section. It will be of a great help
Great explanation!!!
can we have more videos like this by you?
Not now. Maybe in the future. I have a conflict of interest.
Awesome explanation in depth ;)
btw do you have a github repository or blog where i can find your code ?
Awesome explanation..
Nice explanation sir can you make more videos about Naive bayes, KNN, DT. 👌👍
beautiful and a wonderful tutorial
Hi sir, thank you for your video and the very clear explanation, really appreciated. Can i ask for the codings that are used in the video?
mila kya code?
Awesome explanations!
Excellent vdo
Explanation on SVM so perfect. how about if dataset is unstructed and non-numeric data? Is it can follow as the step in this video?
Great job
Please teach to plot hyperplane also
This is so good and helping, but only lacks decision boundary. Any idea?
ThankYou so much. You are saviour.
permission to learn sir. thank you
thank you so much, it was very useful
Thank you Very much ,keep it up!!!
you are the absolute best!
please make a video on SVM on Word2Vector... how to train and test data and prediction result using SVM on word2vec. Thanks
Thankyou so much sir!!!
exellent video
very nice
Sir, please make more videos related to ML
pls don't use mechanical keyboard the sound is so irritating . The video is overall good
well-explained, thanks!
Hello. Thanks for your video. it was really great. I have one question though. does this line mean that only first 200 rows that their class value is 2 will be plotted? I mean we will see only 200 points in the plot?
benign_df = cell_df[cell_df['class'] == 2] [0:200]
Please upload some more videos related to ML
Can we use it for trading?
Bravo!!
Good explanation but please, could you give the name of the book which you've been using during this video?
Thank you so much
superb Sir.
Well Explained. I have faced issue at last. when I code classifier.fit(x_train , y_train) .
given error has occurred. ValueError: could not convert string to float: '?' . could you kindly help me out
thank you for this code sir
whats next after this? how do i use this trained model?
17:00 Why did you take the Clump for x, and unifsize for y, why didn't take another columns of 9 instead of these?
who will demonstrate of how graphs are plotted
THANK YOU!!!
Thank you SIR !!!!
Thanks 👍
can u plz provide the notebook ... with source code
Can I get code??
Can you please explain about radial base function in spam detection in jupyter please
THANX
if at step 6 some of the columns are of integer type and some are floating type then. what to do in this case..
Sir, from where i downloaded this code ?
Thank you
i have one question. what if i want to make a model with svm that contains strings in my attributes?
Share the Jupiter notebook link of this session pls
How can we compute the training accuracy only ? Not the testing accuracy.
what does happen when we have more than 2 classes i.e. multiclass??
Please make some more videos
please how can be calculation time training model?
Iam getting a bad input shape in step 9 can you explain?
PLEASE help me sir I'm getting this error on different dataset....ValueError: bad input shape (166, 61)
Sir I have faced problem to split train and test data set one error is occured like value error about train set is empty
Y we didn't normalise the dataset array before applying the model kernel?
awesome Thanks!
Sorry, can you help me. How to visualize the result with support vector, hyperplane and max margin?
I have a dataset of (only) accidents with both numeric and categorical variables. How can I know with one-class SVM which variables are influencing?
i think u have to first draw a pair plot then u have to see for the best gausian and according to that u have to apply svm for each good gausian attributes, so u will find out what is best influencing
Thanks a lot
My dataset has no numeric value.its a news archive dataset and i want to detect the noveltyfrom this news archive.i want to use SVM.I need a help.Can anyone help me please?
So I think this will be a dataset in for of statements. So you can try to learn them through SVM.
refer to point 6 of the video.u can convert datatype of each and every column.else u can manually convert those non numeric values in the xlsx file.
say if u have attribute color{red,blue,green} then u can change them to color{1,2,3}
Can you share that notebook?
17:00 how do you decide x and y?
cant u make a graph showing the last code?
Sir, I need to know about the hyperplane. SVM is the separation so please plot that graph too or please tell me.
Hi @Anmol, a hyperplane in a 2D plot, would be a simple line (or curve) that can separate the different available classes in the data sets. I will try posting a new video, but meanwhile you can refer this nice blog - chrisalbon.com/machine_learning/support_vector_machines/plot_support_vector_classifier_hyperplane/
@@sudhanshu_kulshrestha Thank you sir
Thanks
THANKS
Hi, Thank you for the explanation. May I know if you can share the notebook.
I have intentionally not provided the notebook so that viewers have to write down themselves. It's just 20 lines of code to write.
I have one doubt can you help me please
There was a significant class imbalance.What about that?
Why have you stopped making new videos
In min 19.08 u just forget to change the label of malignant......
github link please
Sir want your help pls help me🥺