Training a Neural Network in a Spreadsheet

[@ConceptsIlluminated]

To easily make a copy of the template, visit: docs.google.com/spreadsheets/d/1wylBJWZud1R4wcSGdlMsNKRodjhs4KGkMPRK3Zt8hUA/copy

[@rubytejackson]

your entire explanation is exceptional! very intuitive yet retaining the details!

[@JohnFWitt]

This is easily the most illuminating video on neural networks I’ve seen. Great work!

[@SassePhoto]

This is EXACTLY what is needed - THANK YOU 🤟- The downloadable sheets are the icing on the cake - and ev erything becomes crystal clear - well done

[@StevenG22]

I like the explanation of curve fits in terms of your data points “pulling” the curve into the best-fit shape! Nice work!

[@tmitra001]

this was the best explanation on ANN i have ever seen in youtube

[@vid00vid]

Outstanding work on both this as well as the deep NN Excel example. Thank you!

[@rick_falcao]

you saved my life, ty

[@PierreSutherland-c7i]

This is pretty remarkable, thank you

[@jamescollier3]

that's Very cool! thanks! great demonstration; cool way to see all the details

[@desmondwong5851]

Thanks very much for this - really brought it home for me!

[@tim40gabby25]

Hi. Came from Some 3b1b.. your video is the best on the subject. Old UK duffer here :) Subscribed.

[@tarkatirtha]

Brilliant introduction!

[@peasedustin]

This is fantastic, thank you so much!

[@arnutsutha1507]

Excellent, Thank you so much.

[@desmondwong5851]

Fantastic explanation!

[@GodofNow]

It's An #AwesomeVideo #HandToHand Tutorial of #NeuralNetwork #Thanks ❤️

[@blacklistnr1]

9:27 "success", Statistics has a very funny definition of success. - If I need to buy a coffee on floor 10, but only make it up to floor 8, that's a complete failure as there's no lounge or coffee. - Meanwhile statistics with 8, 9, 11, 1000: yeah that looks about right. It's incredible that ChatGPT even produces truthful responses rather than daydreaming statistical averages.

[@almognagar5650]

thanks for this video, learned a lot

[@subtlethingsinlife]

Cmon man , you can't unravel the sorcery of machine learning like that , what will happen to so many creators whose income depend upon making machine learning no less than magic ... You will ruin their business ....

[@samlovebutter]

Breaking News: Big Tech gone broke

[@joshcannon6704]

Man that was an excellent video, but I have one question, if your column “L” is always 1, the. That would mean that that column is entirely unnecessary and can be eliminated, isn’t that correct?

[@joshcannon6704]

Ok so I managed to play with this quite a bit and figured with a couple of these in series, you can create a macro to automate it and continually copy the weights generated after the correction back into the top of the model continuously. I’ve been running it for a few days and creating some good algorithms for some auto stock trading bots I’ve been tinkering with. What I need now is to figure out how to incorporate Fourier functions into this model. If you have any insight please chime in

[@ricarvar]

Thanks a lot for this explanation and example... Is there any way to access the excel template?... the link provided seems not to be working any longer :-( kindly, could you please either provide an updated link or send it by email? - thanks again, great video!

[@ConceptsIlluminated]

docs.google.com/spreadsheets/d/1wylBJWZud1R4wcSGdlMsNKRodjhs4KGkMPRK3Zt8hUA/copy

[@SoaringMoon]

I'm curious as to what the most powerful NN would be given a sample size of various spreadsheet softwares to conclude which would be the best to use for this purpose.

[@ConceptsIlluminated]

For production purposes, I would recommend *no* neural networks be done in spreadsheets :) If you trained a network externally and copied the weights in, I would imagine most spreadsheet software could handle up to hundreds of neurons before starting to lag a bit. Given Google Sheets does computation in a browser but Microsoft Excel and LibreOffice are native code, I would expect the native solutions to scale better into the thousands of neurons or more.

[@andreizelenco4164]

I am a bit confused by the partial derivative of the cost with respect to the activation. In the video this partial derivative is 2(a-y). But the cost function is (y-a)^2 so the derivative should be 2(y-a)?

[@ConceptsIlluminated]

I think there is an extra negative sign folded in from wanting to go "downhill" towards the local minima.

[@andreizelenco4164]

@@ConceptsIlluminated Thank you for your answer. I have to admit, my calculus knowledge is poor. I think the partial derivative of cost with respect to the activation is correct in the video. I can't confirm it for myself because my lack of knowledge but I asked ChatGPT and it gave me the same result as in the video.

[@mathyustrod6776]

Hello, Kevin! I'm new to NN, and your vid is fantastic. Any thoughts on how to implement NN to predict component wear measurements? I have data collected at irregular intervals. Thank you!

[@ConceptsIlluminated]

I would suggest asking this question on the r/neuralnetworks subreddit. Include some sample input data and desired output. The folks there are much more knowledgeable than me and can hopefully guide you better.

[@mathyustrod6776]

@@ConceptsIlluminated Thanks, Kevin!

[@pmesple]

Hi Kevin, I downloaded the spreadsheet and populated it following the video but when I uncover the activation chart I don't see the same chart as in your video. It seems not to be working. Do I need any add-in so that the chart shows the result? many thanks for the great video!

[@ConceptsIlluminated]

When you say "download", do you mean "download and use Excel" or "made a copy using Google Sheets"? I did not test the sheet with Excel.

[@lilivandermeersch2918]

@@ConceptsIlluminated Thank you so much for this video. I can hardly believe that finally I get this topic. I have the same issue as mentioned above. I made a copy using Google sheets and then downloaded and modified the Excel, hence the activation charts don't work any more. Could you explain how to recreate them in Excel if you have the time please? Many thanks.

[@multiarray2320]

what is the reason for squaring the cost function? for numbers smaller than 1 squaring has the opposite effect than for bigger numbers.

[@ConceptsIlluminated]

I believe it's to make the result positive. Why not use the absolute value? *vague mutterings about differentiable at all points*

[@multiarray2320]

@@ConceptsIlluminated thanks!

[@learning_with_irving4266]

How do you use that for a demand function

[@choudharyom1]

thankyou

[@meowrel]

I LOVE YOU

[@NavySturmGewehr]

Can you cover how you made the activation chart?

[@ConceptsIlluminated]

Sure thing - it is a Bubble Chart with values from 0.0 to 1.0 on the X and Y axis (using increments of 0.1) The series for the chart is the value obtained from the weighted sum of X and Y using the bias, weight 1, and weight 2, rounded to the nearest 0.1. I also needed to draw a few points off-screen (-100, -100) so I could have a different shade of blue for each of 0.0 through 1.0. Finally, I set the size of those offscreen bubbles to 10, and the on-screen ones to 1.0, which made the appearance of mostly filling out the chart. If you make a copy of bit.ly/NNsheet, look at the Interactive AND sheet, and unhide columns M and beyond, you will see all this in action.

[@NavySturmGewehr]

@@ConceptsIlluminated Thank you very much!

[@craigmunday3707]

Text is so small, you have the entire screen to magnify the work