If you're just using the algorithm to suggest items customers may be interested in buying, the math might not be important because nobody loses much when a mistake is made. Sometimes the stakes are higher and it's important to know what's really going on. If you're using an algorithm to decide who to give a loan to, all those "unimportant" small details might turn out to be very important once it's too late.
For me in Chrome on OSX you do get a visual representation of the neuron's input when hovering. It shows up behind the data points in place of the neurons' output when hovering.
Okay, so it works by minimizing (equiv. maximizing) some function. But that doesn't say much about how it "learns" the gradient. What function does it care about? Average squared error (predict_prob-Z_i)^2 ? Average absolute error? The likelihood function of some assumed distribution? Maximum distance between the classification border and closest observed points? If I saw someone carrying a bag full of blueberries and some bread home from the grocery store and asked to know how they chose to buy that, to which they replied "I had a list of characteristics which I thought where important for groceries to have in this trip to the store. For each grocery item, I recorded a vector of degrees to which the item possesses each of those characteristics. Finally, I chose the group of groceries that had the best combination of degree vectors", I still wouldn't really know anything about why they bought the blueberries and bread.
>if we can't forbid citizens from photographing in public, why should we forbid our government?
I don't understand this comparison. The very fact that the surveillance is being done by the government changes the meaning of the action. Citizens don't have the power to do anything with the information they might gather through surveillance. Citizens don't have the ability to force all other citizens to pay them more money for funding surveillance programs of ever-increasing scope. Citizens have jobs which exist to serve a real need that exists in the economy, and so realistically wouldn't be doing anything of the same magnitude unless there was popular demand for it.
>My visceral reaction to grammatical errors is the feeling that the person places less of a value on communicating ideas. It isn't about intelligence, it's about values.
I don't see what the usual "grammar pedant" complaints have to do with valuing communication. I typically see people complain about things like using "there" instead of "their", "its" instead of "it's", "affect" instead of "effect". As a rule, none of these things have any impact on the ability of a reader to understand the writer's intended message. I realize that in some rare cases these mistakes create ambiguity, but that's never the grammar pedant's complaint.
>t would be reasonable to say that CAPM is a mathematical result, and the evidence suggests the mathematical model required for CAPM simply fails to correspond to reality. But many finance folks, especially in academia, won't admit it.
In other words, "Things are more complicated in real markets". I don't see any problem with wanting descriptive theories. Economists are interested in building models whose parameters can be tweaked in ways that correspond in a clear meaningful way to a possible actions (e.g. change government expenditure on X by Y). If you try to just maximize predictive power you're missing the point. Economics can be used to predict the future, but I would say the main goal of the field is to produce theory that will provide valid methods of altering the future.
I use Desmos all the time, both for my own work and as a tutor, so thanks for the great resource! Is there any plan to make a version for bivariate functions? It would also be awesome if you could just paste a function written in LaTeX into des is to get a plot.
Creating an 100(1-a)% interval estimate of the population mean based on the sample's mean and variance is equivalent to examining the set of all values which produce a p-value below a%. Your view of the way Alice and Bob should be making inference about the true mean is actually exactly what hypothesis testing is. It's just that there is often a "status quo" belief about the parameter which has important theoretical implications. And academic papers are usually about that belief specifically, so it makes sense that they talk about it as a "hypothesis test". And that's the logical headline, the statement about the specific value. But standard deviations and distributions are often given, making it trivial to create the interval as a reader.
>Hint: doing big studies just so you can fail to find an effect is nonsensical. Instead, do big studies so you can put a tight upper bound on the effect. Don't tell me that vaccines don't have a significant (or discernible) effect on autism. Tell me that, with 99.9% confidence, you have ruled out the possibility that vaccines have caused more than ten autism cases in the entire history of vaccines, and that, most likely, they've caused no cases whatsoever (or whatever the right numbers are).
Checking the bounds of a 100(1-a)% confidence interval is exactly equivalent to checking for a p-value below a%.
My main goal in life is to be happy. I have other goals, but if working on them for the n-th straight day comes in conflict with my main goal, I'm gonna take a day off.
I don't think multinational corporations are going to change their entire product line entirely on the basis of gossip about "the next big thing". Maybe some would, but surely not all. A decision like that would have to be made after doing some serious market research and testing sales of products with that feature against sales of products without it. If corporation A switched to only IoT devices and customers didn't want that, surely Corporation B which hasn't made the switch would gain more market share, then A would take note and switch back. There's too much money to be made by being the one company that still offers what consumers want. I don't understand this fear that profit-driven corporations will suddenly decide to add costly features in a world where no one wants them.
If no people want or will use IoT connected devices, what motivation do companies have to sell only IoT devices? I don't understand the logic behind this prediction (only IoT products available, but no one wants them). It seems a bit like predicting that in the future people will still prefer to write on paper, but no companies will sell paper anymore, only tablets. Maybe there's a key motivating factor I'm missing?
Apple doesn't advertise it, but the iPhone 6 is pretty water proof. In this video it was left in the water with the screen on for >20 minutes and all happened was the speaker stopped working.
There's always the Wolfram Alpha app. Or if you want something offline, you could use SymPy (though obviously this isn't a touch-device app). I use Wolfram Alpha on my iPhone pretty much every day for simple matrix calculations, derivatives, integrals, and summations and it works very well.
Judging from the fact that Google automatically redirects gmail.com to inbox.google.com once you've visited inbox, I'd guess they view it as the next-gen Gmail interface.
I think background app refresh may be separate from location services, and facebook still tracks your location in the background. Try also turning off location services for fb (or set it to only when in use). Settings>Privacy>Location Services
I can't comment on whether it's the best for the platform, but I don't think there's much of a cognitive burden placed on iOS users by material design. A whole lot of iOS users use the Google Maps and Youtube apps, and many also use Gmail/Inbox for email, and Chrome as a browser. My Grandmom uses Google Maps and has never had to ask me any questions about how to do things with it.
I think this is because the shirt is stretched horizontally just from being worn but obviously there's no forces stretching the shirt vertically because any force that would stretch it vertically just raises the bottom instead
That most of us have times we dedicate to thinking about the things that make us money and times we dedicate to thinking about other things? I'm not sure what's wrong with that. Obviously we don't have the strict control to turn our thoughts completely on or off so this doesn't preclude what might be considered "background processing". Still, surely it is reasonable to dedicate some times to some things and other times to other things, even if the things in question are creative processes. For most people, deciding "I'll just work through this new research topic whenever I spontaneously happen to be thinking about it" is probably not their best way to contribute to the field.
Of course academic work is creative work, but saying "there's no off switch" is too simplistic. Academics are people too. They prepare meals, watch television, spend time with their kids and spouse, go grocery shopping, go out for drinks, and visit mindless entertainment websites just like the rest of us. They may happen to think about their work during those activities but ,if they do, it's only by accident. The question of how much time they spend in these "leisure" activities vs "work" activities is well-posed enough to have a useful answer. And of course it varies from week to week but that doesn't mean we can't talk about what the distribution looks like. A professor whose average workweek is 60 hours lives a different life than one whose average workweek is 40 hours.
For Facebook Messenger on iOS , the "return" button on the keyboard only creates line breaks. To send the message you have to click the send button above the keyboard.
I think it's just as clear as the typical cruise control indicator, and the failure to notice that has similarly serious consequences (If you think cruise control is off when it's on you're likely to hit something pretty quickly).
In the meantime, you can always just load the html and delete the div elements for text and controls (to take a screenshot). Obviously this makes the "arbitrarily sized" part harder but now I have a nice wallpaper for my phone.