Complete Machine Learning Course in 60 Hours - Part 3 | Full Machine Learning Course for Beginners

. This Complete Machine Learning Course video will help you understand and learn Machine Learning in detail. This Machine Learning Tutorial is ideal for both beginners as well as professionals who want to master Machine Learning concepts & practice.

Timestamp for the topics covered in this Machine Learning Course video:

00:00 Introduction
03:25 Linear regression - Intuition
32:30 Math behind Linear Regression
52:25 Gradient Descent for Linear Regression
1:10:51 Building Linear regression from Scratch
2:00:31 Implementing Linear Regression from Scratch
3:04:18 Logistic Regression - Intuition
3:26:34 Math behind Logistic regression
3:43:53 Loss Function & Cost Function for Logistic Regression
4:12:53 Gradient Descent for Logistic Regression
4:32:31 Building Logistic regression from Scratch
5:37:39 Implementing Logistic regression from Scratch
6:06:42 Support Vector Machine (SVM) - Intuition
6:22:22 Math behind Support Vector Machine
6:54:05 Support Vector Machine - Kernels
7:13:47 Loss Function for SVM
7:35:52 Gradient Descent for SVM
7:54:07 Building SVM classifier from Scratch
8:58:55 Implementing SVM from Scratch
9:57:04 Lasso Regression - Intuition
10:17:58 Math Behind Lasso Regression
10:40:01 Gradient Descent for Lasso Regression
10:58:28 Building Lasso Regression from Scratch

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[seththunder]

I know you put so much time and effort into these videos and I really would like to say that we are benefitting a lot from it. From the very bottom of my heart, thank you so much for these quality videos. You are always the one I tell about when someone asks me about machine learning

[abc_noob]

Also do this for DL too and also for CV and NLP too please sir 👌

[geraldbelizaire]

Really good quality video, thank you for this training. Good and very clear explanation.i watch it until Gradient Descent, and it is really a valuable work. Thank you.

[commonguy]

WAITING FOR PART 4. PLEASE UPLOAD IT BY TUESDAY. PLS

[karanagrawal]

Pls also add the implementation of Lasso Regression as well

[cximyvo]

I saw all the descriptions of all videos, what about other supervised unsupervised models ?Deep learning Models? Are there any other separate play lists for them or any other tutorials for them? I want to learn that concepts also and i like your explanation.

[varshinimanchikalapudi]

hello, i find usefull for your content.can you please make same kind of series for artifical intelligence and deep learning

[souvikbose]

Is it required to learn how to build algorithms from scratch, or just knowing how to implement is enough ???

[shortclips]

you dont cover codes for lasso regression. i mean you have covered from scratch but not from the in built libraries as you have done in other models. By the way that you, your videos as awesome.

[anishkuvelkar]

hey, i had a doubt. How do we know when to stop with the gradient descent in linear regression, i mean u didn't put any stop conditions, so in 1000 iterations, how does i select the best value from it?

[rohitsingh]

Machine learning course live Lao na sir

[idabagusmadeswarbawa]

Is there learning vector quantization method?

[Ts_kashyap]

Bhaiya I have a question ⁉️

When we try to find the global minima in gradient decent let's say in linear regression, then how does our algorithm (partial differential equation) knows that it has achieved the global minima. I mean I get how it keep reducing the cost function but did not get how does it know that global minima has reached and now it has to 🛑 stop. Please reply I'm a bit confused . And thankyou for this wonderful course.❤

[commonguy]

why are we building linear regression instead of builtin linearregression model?

[likithanliki]

bro please explain kmeans and kmeans++ detaily

[gauravshukla]

After completion of this courses how many experience I show in my resume

[commonguy]

the video and audio dont match in some videos

[FieldDebby-oh]

Walker Ruth Miller Patricia Miller Kenneth

[anishkuvelkar]

In lasso and SVM where have we used the cost function?

[anishkuvelkar]

Hey, what if some weights value in the same cokumn are positive and negative, you have defined it as w[i] >0, how is this possible, can u clarify please?