153 - Artificial Neural Networks - Explanation for those who understand linear regression

Want to learn about artificial neural network (ANN) from the perspective of linear regression? This tutorial explains ANN using heart disease data set and walks you through the process of calculating results using trained weights and biases.
Code generated in the video can be downloaded from here:
github.com/bns...

[@hemanthchenga5671]

one of the best CZcams channel to learn deep learning, kudos to you sir.

[@DigitalSreeni]

Thanks :)

[@srikanthpvr4161]

Excellent info which evry new learner should know how classicl machine learning to be used in NeuralNets.Presentation is superb and crisp

[@rshaikh05]

excellent sreeni. I wish i had come to your channel before. now there is so much content that its overwhelming! but your explanation is so good with short videos covering only few concepts at a time and that makes it all manageable...

[@vzinko]

just to be clear and for others' benefit, standard relu is not used in the output layer for nonnegative regression problems

[@manasranjanpanda9859]

Thank you so much Sir, Indeed you’re a great teacher and being a PhD scholar in Hydrology I have attended machine learning course to use it in my research work but I am so grateful to you because you explain everything in such a way that a layman can easily understand...

[@DigitalSreeni]

I was layman once, and still am... so I feel your pain. This helps me structure my content accordingly.

[@brunospfc8511]

Great video, i'll recommend , and watch again

[@samarafroz9852]

Best tutorial of ANN

[@DigitalSreeni]

Thanks

[@charchikasinha]

Very thorough explanation! Did have that aha moment :)

[@gh.g1084]

Thank you!

[@frankdearr2772]

Hi, usefull, perfect informations about how it works. great lesson, thanks a lot :)

[@sumitmaitra]

Very nice video.

[@samarafroz9644]

Your videos r literally best sir

[@DigitalSreeni]

Thank you so much 😀

[@RajeshSharma-bd5zo]

Amazingly explained!!

[@DigitalSreeni]

Glad you think so!

[@larrysummer2015]

Great video.. One question what activation function are you using in the last or output layer?

[@larrysummer2015]

Please suppose I got negatives in my target.. What should be my activation function

[@dilipgyawali1776]

for this tutorial... which one is the dataset?

[@abderrahmaneherbadji5478]

I appreciate your efforts

[@DigitalSreeni]

Thanks a lot

[@mohamedramzyibrahim6375]

Hello, thank you for your efforts. I want to ask you to explain RCNN, faster RCNN, Faster-RCNN, RNN and LSTM with their implementations. Thanks very much for your help and i hope you could answer my comment and explain them. Your explanation and code snippets helped me in alot of understanding and going deeper in cnn and feature extraction methods.

[@DigitalSreeni]

I'll do LSTM soon. I have to find time to experiment with RCNN on real datasets before I can record videos. I do not like to use standard datasets, you can do a google search to find many such examples. For custom datasets I do not have labeled data in COCO format. This is the reason why I haven't done RCNN tutorials.

[@aomo5293]

HI,
For the mse you have used: np.mean(y_test-y_predicted)**2, I think this is error;
mse = np.mean((y_test-y_predicted)**2)
Thank you

[@bheemannanayak6728]

Hello sir, i have only one variable is there that is Age Dependency ratio data so how to do prediction for next 10 years using Artificial Neural Network.

[@1980chetansingla]

Sir you are genius

[@prasadbhadane608]

Thank you so much sir!!

[@DigitalSreeni]

Most welcome!

[@raihananuralya8330]

Hi sir. I still confuse about using ANN on linear regression data (on x and y). Better i use the code on this video or at your '155' video?
Thank you!

[@abderrahmaneherbadji5478]

Hello Sreeni.
Please let me know, how we can use SVM classifier to classify deep features (CNN) instead of softmax function.
Thank you.

[@DigitalSreeni]

I’ll record a video on the topic, stay tuned.

[@flanker6212]

Thanks!

[@DigitalSreeni]

Thank you very much for your support Flanker6. I really appreciate it!

[@efremyohannes2334]

Hello, your video helped me a lot, thank you. Could you please work video on Bi-directional RNN-LSTM for the text line recognition?

[@DigitalSreeni]

A couple of LSTM videos are coming, so please stay tuned.

[@nguyenhongthai2970]

Thank you for sharing, nice tutorial
Sir, can you make a video about medical hyperspectral images?

[@DigitalSreeni]

Never worked with medical hyperspectral images. Where can I learn more about them?

[@nguyenhongthai2970]

@@DigitalSreeni sir, it's just my suggestion. I learned a lot through your channel. Probably from science papers, I think the data type of hyperspectral images is the same as RGB images, instead of 3 channels, now we have hundreds of channels as wavelength bands.

[@motriz-industrial6846]

Very clearly explained! Thank you!
Been trying to find the equation for this data:
drive.google.com/drive/folders/1LpLXfQLYWur0I29MmJBbm01f5fWsBcxL?usp=sharing
I wonder if there is something that today’s technology (software) offers to turn this data into a model.
Can neural networks do it?

[@DigitalSreeni]

Not sure what you are trying to achieve here. The data shows some numbers jumping up and down. There is no visible pattern in the numbers, seem to be rather random. Not sure if there is any periodicity but you can try any of the time series forecasting approaches, like ARIMA.

[@motriz-industrial6846]

Thank you very much for taking the time to respond.
Those are shaft rotations (in Degrees) that move a mechanical arm through a stepper motor. An expensive PLC runs the required motion using that data without problems, but if I could find the equation, I could use a very inexpensive PLC. I will take a closer look at ARIMA. Thanks again for everything.