Neural networks tutorial: Fully Connected 11 [Java] - Some projects

So...

I've had nearly no time in the past but I kept working with neural networks and I finally created a more powerful structure for neural networks to implement different activation functions etc.

I will start with that in the next video.

The problem with the sigmoid function: Gradient vanishing (if you want to read more about it and how to fix it) (Otherwise I will do that soon (probably))

[baguettex]

I can't say how great the videos of this series are, although java isn't great for machine learning, this definetly pushed me toward learning more about it!!

[vladisoul]

hi man amazing lessons . just one question ...how did you use your input in this program? where have you add the input (learn input and teach input)?

[julianabhari]

Is it possible to turn this fully connected network into a convolutional neural network? If so how would that work?

[socketbyte]

IntelliJ is pretty weird when it comes to console output, it sometimes eat one line or smth. I always test in a standalone .jar artifact, so it works flawlessy.
PS: Your project is pretty nice, I will try to do something similar later.

[socketbyte]

I've been thinking lately how powerful is Samsung 8K AI technology. Just imagine, 8K -> 7680×4320 is 33177600 pixels. We have here only 28x28. Their input data is huuuuge haha

[jagartidev]

Thanks for putting this series out there! I've been interested in NN for a while but didn't know where to start. Java is my main language so this should be a good exercise to get into it. I haven't completed the series yet, though. In fact, I watched this video second, then 10, then 9, and then 8, before I realized that your playlist is backwards, haha. So.. thanks, again but you might want to recreate the playlist.

[necromanhd]

Interesting video. I'm looking forward to the next tutorials :)

[anizivzivadze]

How can I get that guy's UI implementation for drawing the numbers? I could not find the code in his channel :(

[SmartoK]

Hi, @Finn Eggers ! Just wanted to say that your tutorials are amazing, helped me a lot in understanding the "coding" part of the NNs. I am really impressed with your project, i.e. visualization of a NN working process by plotting dots and then grouping them by coloring the area nearby. Just wandering if there is any possibility to get the access to the full code for this example? In any case, thanks again :3 and keep it up!

[EndersupremE]

Hey man, first thing, excellent videos. I learned hell alot about neural networks, which I needed because of college and stuff.
So, I´m working on a regression type neural network, and I realy didnt know there was this difference with ur type of network until a ran tests and searched up things. I was wondering if ur still into this and could maybe make a video of a regression type network? Or if u know a video of someone doing it in Java and explaining real well like u do. Im searching on how exactly this linear regression thing works but most of the videos use other program languages and dont explain realy well.

[freebtcforall]

Great video series! How do you know how many neurons should be in each layer? My intput layer has a size of 300 and the output layer 2. (from index 0-149 five of the inputs will be 1 and the rest 0, (same for index 150-300). Currently I've tried to use 300-600-100-2 for my layers, but did not get great accuracy. Given enough training time, should I add more neurons/layers or less?

[yeeeeeet]

how about a small competition?
my Network(784, 300, 120, 60, 10) i trained it like a few hours and now it identifies 29950 / 30001 pictures correctly...
did someone got a better Network ?