SVM (Support Vector Machine) in Python - Machine Learning From Scratch 07 - Python Tutorial

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In this Machine Learning from Scratch Tutorial, we are going to implement a SVM (Support Vector Machine) algorithm using only built-in Python modules and numpy. We will also learn about the concept and the math behind this popular ML algorithm.

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[mantidream]

Finally a straightforward guide. Thank you

[ozysjahputera]

Do you plan to offer a tutorial video on non-linear SVM with the kernel trick to extend the linear SVM to handle non-linearly separable data?

[VoteU]

It is very usefull for teachers as well as students. Thank you sir

[nikolayandcards]

As always, great video. Everything is getting clearer and I feel I am getting a better grasp of it.
However, this SVM implementation considers linear separation of the data, am I right?
For non-linenar separation, the math would be different, or am I wrong? I didn't see Kernel functions and Lagrange Multipliers being used in this implementation. Could you give me a bit more insight?

[aadya]

Explained properly. Thank you for this.

[andrianarutyunov]

8:02 Just to make sure, that I understand it properly:

Doesn't it have to be the k-th component of x_i instead of just x_i ?

[ashiqhussainkumar]

I've already done linear and logistic regression Mathematics in detailed fashion, here the life becomes far easier ...
Exact same concepts only hypothesis function differs

[thecros]

can you please guide me with maths needed fro this any papers to read please i really need to get the cruks of the maths behind

[blackpearl]

what if you want to add a csv dataset sir

[huojinchowdhury]

Why do we multiply class labels with linear functions?

[hirenkakkad]

Superb. Can you please share code or videos for other kernels like this? It will be a great help.

[LIMLIMLIM]

When I test this model with sklearn iris dataset, I get accuracy of around 0.3. While using the sklearn svm.svc gives very high as in 0.9. What is fundamentally different from sklearn model from this one?


Thank you for the great tutorials

[mangilipallylaxminarayana]

Thanks a lot man, this video is very beginner friendly. Liked and subscribed.

[abhinava]

Nice video sir.
Can you make videos on Fuzzy classifiers like FCM, PCM, etc?

[mariav]

Can you recommend a paper or book that teaches the math of SVM? That is, that follows the steps you describe in the video?

[pinakidasgupta]

could you make it for more than two classes?

[justAdancer]

Is it applicable for testing dataset with multiple class instead of two?

[babaabba]

Hello what if we are dealing with more than 2 classes? how shall I approach the problem

[dwardster]

You can add this code to the training loop to print the hinge loss cost every 25 iterations:

if i % 25 == 0:
cost = self.lambda_param * np.linalg.norm(self.w)**2 + 1 / n_samples * \
np.max(np.c_[np.zeros(n_samples), 1 - y_ * (np.dot(X, self.w) - self.b)]) # hinge loss function
print(f"{i : <15}{cost : <25}")

[nadabu.]

Great work. Thank you. I have a question regards equation f(x). Is f(x) = w*x+b or w*x-b. I checked many resources equation of a line is w*x + b