Complete Machine Learning Course in 60 Hours - Part 5 | ML Deployment & Deep Learning Use Cases

. 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
6:04 Anaconda & Streamlit Installation
19:57 Deploy ML model using Streamlit
1:00:10 Multiple Disease Prediction System
2:08:16 Public ML Web App on Streamlit Cloud
2:27:09 Public ML Web App on Heroku
2:45:18 Deploy ML model as API
3:28:22 Deploy ML model as Public API using Ngrok
3:49:11 Deploy ML model as Public API using Heroku
4:13:45 DL 1. Breast Cancer Classification using Neural Network
5:34:50 DL 2. Image Data Processing - Concept
5:54:55 DL 3. Image Data Processing - Python Implementation
6:35:35 DL 4. MNIST Digit Classification using Neural Network
8:06:09 DL 5. Dog vs Cat Classification using Neural Network

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[tejareddy]

Siddhardhan, you are such a beautiful person. This channel will helps to many people who don't have lakh of confidence and guidance. Paying thousands of money to online platforms and realizing there is no use of it . Really appreciate your work and god bless you🙌

[sayande]

Today i mark my completion of the whole 60 hrs course and I have been going through several contents for machine learning on the internet but i believe this course provides perfect blend for both theory and practical implementation of all the fundamental ml concepts, for a beginner I would encourage all to go through this course to have a strong base in ML concepts. In the end, I would like to thank Siddhardhan for his commendable effort for making this video, Thank you.

[raidenshogun]

I Can't thank you enough. You ae the absolute best youtuber in the platform. Lots of love bro.
I pray you have a bright future ahead.

[letsupdate.]

We see you put lot efforts in making this video, it's complete machine learning video without even a single points. Great

[mr.twente]

I just wanted to say a big thanks for your amazing playlist! It really helped me a lot in understanding the subject, and I’ve learned so much thanks to your clear and easy explanations. I followed the whole series, and it’s been a game-changer for me.
Appreciate all the hard work you put into making it. Keep up the great work sir, thanks alot sir❤

[telher]

Thanks for an amazing course. I stumbled on one of your videos while trying to find answers to my assignment and that video was extremely helpful.

Then i saw you had this course uploaded. I'll follow through on each video and leave feedback as I complete each step. For those interested in knowing how it goes, you can watch this space.

[elyntro]

Hats off to you sir, great content really appreciated keep growing sir . All the best !!!

[dhruvin]

Thank you soooo much sir😇😇😇😇, for your hard work. You are awesome😊😊

[zouairisaim]

Good job sir i'm thankfull so much

[MUSTAFAADNAN-oobr]

Hi I want to get the course files in PDF format. How can I do that?

[gamininishantha]

Thank you sir.i'm successfully completed this tutorial searies❤️😌.what i learn next🥰i hope you definitely answer this🙂

[whoiamagain]

Wait did I just stumbled upon gold mine 🙌

[sbvforworld]

You will never be ready so just dive in ~SBV

[JohnCena-xznz]

Have you completed unsupervised and reinforcement learning?

[abhishekkar]

Thanks alot for the videos.Is there any part 6 of the same playlist?

[adnanmerchant]

Just wanted to ask that if i watch entire 60 hours will i learn everything in ml?? and will i be internship ready?

[swarantejvajrapu]

Heroku is asking for payment. What to do??

[mysterioushermit]

Which all ml algorithms are covered in this 60hr course?

[bhuvanesh]

Only instances of `keras.Layer` can be added to a Sequential model. Received: object at (of type <class


how can i solve this error

[imma_Akash]

I can't find the deep learning course