Increase the learning rate of your optimizer. Something else you could try— look into “back propagation” to tune your learning rate after each layer.

I heard a great explanation of this recently on the news. It’s a number that (taking a bunch of other things into account like payment history for bills including mortgage, loans, etc, credit history (mainly think “how long have I had and used a credit card) and other factors into 1 number from 300-800. This number tells people “how likely am I to pay back credit?/how good of a borrower am I? (From a bank’s perspective$” the higher the number, the “better” of a borrower you are.

This is important and you should care because those with higher credit scores:

• can get lower interest rates when you go to get a mortgage
• would actually qualify for higher loan amounts/can borrow more money, and a bunch of other stuff.

I might be off base here but my first thought was there might be something there with integrating the full area of peaks and sorting out peaks from specific elements in the spectral analysis of a heterogeneous mixture (possibly through a Fourier transform or convolution? This is ringing bells for me as feeling similar to signal processing…)

The “line down the middle” is where the “predicted” shark is the true shark (the type of shark was guessed correctly. The color of the square represents the certainty of the guess. *How confident is the software that it made the “right” guess? In these cases, it’s 100% confident since it is the right one!)

Pretty cool if you ask me!

You can match them up to see for yourself.

I think I’m gonna have to respectfully disagree on a lot of this. You’re right that it largely comes down to training data used. The thing that largely jumps out to me, though, in the examples you give and in your point (1) is that while you want to train using a large amount of data, especially for such large networks as those you suggest, is that while you need that large amount of data, you want to avoid overfitting your model to your data in the pursuit of accuracy or reliability or whatever metric you choose to determine how “good” or accurate your model is against some ground truth.

And while on the surface, NNs can definitely seem like or appear as though they’re “black boxes” or “we can’t accurately describe their structure or how they work”. That’s largely untrue. In fact, I would claim that it’s precisely because we can design and model NN structure and use a structure (both in terms of # of layers, connectedness between them, inputs, weights, biases, activation functions, etc.) that would lend itself best to a given purpose, that has allowed the field to come as far as it has, to generate the NNS in the examples you provide in the first place.

Sorry about the rant… I didn’t realize I get so passionate about NNs.

Check this out. I’m doing AI research and there’s this paper on DenseNets which can be used in, and are directly applicable to, NLP.

There are definitely blood tests they can do to detect markers for certain cancers but it’s impossible to tell if they did the test for leukemia if we don’t know what the test is called… what is the test called that they did?

Hemoglobin carries oxygen to every cell in your body. Low hemoglobin means less oxygen is getting to your cells. Different cells can go do long without the optimal level of oxygen they need, and so, those parts of your body get damaged. The amount of damage done to different parts of the body determines the effect on your overall health. Since certain parts of your body have really important functions and a high demand of oxygen (your brain, your heart) this could have especially bad long term effects.

This doesn’t cause traits to be one or the other, but it’s related to

1. How prevalent is that trait in a population?

And

2. Does that trait make the thing that has it more successful at passing down its traits* or less successful at it?

*”passing down traits” == “making babies”

They’re really useful with electrical circuits (which, if you use a phone, car, or anything else powered by electricity, is something you should care about)

“Controlling the blood” is what buffers do (for blood pH).

Buffers don’t split water into H3O+ and OH-, that happens from stomach acid… buffers are in your blood… (and water has already been split into H3O+ and OH- before those molecules get to the buffers).

Yes. And back to your original questions…

Yes water molecules get protonated to form H3O+. These molecules get filtered out into blood from capillaries in the small intestine as part of digestion.

Then, in the blood, the amount of H3O+ gets really tightly regulated (turning between H3O+, H2O and OH-) by a bunch of specific molecules that are called buffers (a sort of category of molecules) that regulate the pH of your blood.

If the pH of your blood falls too far out of this range, by having too many/few of these H3O+ molecules, or a breakdown of the above process/other molecules involved, having too few/too many buffers, etc. that can be very deadly, very quickly.

Stomach acid is a very low pH, yes. But your stomach doesn’t always just have acid hanging around in it when it’s empty. (There are separate organs that create, store and secrete stomach acid into the stomach specifically when it’s needed and in response to certain hormonal processes, or other factors).