How do you establish an exact mapping to sth that is not exact, but only a buzzword term under which different people collect different methods? Well, not that important. It's only important that the buzzword appears in…
Well, there is more. E.g. abbreviating deep belief nets with DBM, which is the commonly used acronym for deep boltzmann machines. These are similar, but very different. Calling an RBM an encoder is somehow not far…
This has been done since the 90s. The Deepmind paper is about a few more tricks.
From Wikipedia: > Engineering is the application of scientific, economic, social, and practical knowledge in order to invent, design, build, maintain, research, and improve structures, machines, devices, systems,…
Yes. Also the guy does not seem to be that knowledgeable. He did not get the memo that more input data can lead to worse results; he claims the opposite in a slight variation (i.e. the more precise the input data, the…
I think the difference is that Prolog was aimed to solve all kinds of programming problems. PPs on the other hand is very domain specific from the start.
e.g. fuzzy logic.
Give me Mathjax and I'm in.
FTFY: this was accepted at the nips software engineering workshop. (not the same!)
> A 'predictive model' should say 'if you do X then you will end up with Y' - and the X cannot be adjusting some number. The X has to be stuff like 'building ETU's in West Africa', or 'canceling all flights',... A…
The problem is that this guy has no clue. - A naive Bayes classifier is not a Bayesian method. It's just using Bayes rule, while Bayesian methods marginalize out the parameters. - Regression and classification are…
You cannot distribute it with 100% accuracy right now. Given the BMI assumption proves true, you will be. Thus, you can spread copyrighted material. Big difference.
Don't think so: it would hide the correlations, which are especially interesting.
I did not even get to that because I could not concentrate.
Also, A x B is not used for dot product in the math world. That is mostly cross product, and might trigger wrong associations.
Animated pictures of a Jump'n'Run game make blog posts really hard to read. Might be related to the way human attention works, but well.
> Brains work probabilistically at least in the sense that the underlying biomechanics have some statistical distribution. No, it's us that use these distribution to model them. Reality might be deterministic after all…
Deep learning research cares neither about identifiability nor global minima. Mostly, local minima are good enough to get the "job" done; here job is the task you are trying to solve. In fact, it is easy to show there…
Whatever the uni. He was working at IDSIA, one of the main contributors to deep learning. Also, his advisor, Markus Hutter, did some serious stuff on AGI.
Also: aerodynamics is not really hard, anyone can fold paper planes! Or: programming 3D games is easy, just build new levels for an old game! Or: I don't know what I am doing here, but look, this photoshop effect looks…
Physics is pretty close to data science. In the end, physics often is about applying the scientific method to sth. Traditionally, sth is "the world", but it's not too different if it's just another set of data.
> Plus, not a minus. I think the 13" MacBook Air is the best laptop on the market today. Tight integration between hardware and software is key. Sorry? How is a restriction a plus? Can you use a Lenovo with OS X? No.…
Makes it sound as if those things were mutually exclusive. They are not. I don't like the attitude of this article. Good soft skills will not compensate lack of smartness. This might not appear in a job interview…
How do you establish an exact mapping to sth that is not exact, but only a buzzword term under which different people collect different methods? Well, not that important. It's only important that the buzzword appears in…
Well, there is more. E.g. abbreviating deep belief nets with DBM, which is the commonly used acronym for deep boltzmann machines. These are similar, but very different. Calling an RBM an encoder is somehow not far…
This has been done since the 90s. The Deepmind paper is about a few more tricks.
From Wikipedia: > Engineering is the application of scientific, economic, social, and practical knowledge in order to invent, design, build, maintain, research, and improve structures, machines, devices, systems,…
Yes. Also the guy does not seem to be that knowledgeable. He did not get the memo that more input data can lead to worse results; he claims the opposite in a slight variation (i.e. the more precise the input data, the…
I think the difference is that Prolog was aimed to solve all kinds of programming problems. PPs on the other hand is very domain specific from the start.
e.g. fuzzy logic.
Give me Mathjax and I'm in.
FTFY: this was accepted at the nips software engineering workshop. (not the same!)
> A 'predictive model' should say 'if you do X then you will end up with Y' - and the X cannot be adjusting some number. The X has to be stuff like 'building ETU's in West Africa', or 'canceling all flights',... A…
The problem is that this guy has no clue. - A naive Bayes classifier is not a Bayesian method. It's just using Bayes rule, while Bayesian methods marginalize out the parameters. - Regression and classification are…
You cannot distribute it with 100% accuracy right now. Given the BMI assumption proves true, you will be. Thus, you can spread copyrighted material. Big difference.
Don't think so: it would hide the correlations, which are especially interesting.
I did not even get to that because I could not concentrate.
Also, A x B is not used for dot product in the math world. That is mostly cross product, and might trigger wrong associations.
Animated pictures of a Jump'n'Run game make blog posts really hard to read. Might be related to the way human attention works, but well.
> Brains work probabilistically at least in the sense that the underlying biomechanics have some statistical distribution. No, it's us that use these distribution to model them. Reality might be deterministic after all…
Deep learning research cares neither about identifiability nor global minima. Mostly, local minima are good enough to get the "job" done; here job is the task you are trying to solve. In fact, it is easy to show there…
Whatever the uni. He was working at IDSIA, one of the main contributors to deep learning. Also, his advisor, Markus Hutter, did some serious stuff on AGI.
Also: aerodynamics is not really hard, anyone can fold paper planes! Or: programming 3D games is easy, just build new levels for an old game! Or: I don't know what I am doing here, but look, this photoshop effect looks…
Physics is pretty close to data science. In the end, physics often is about applying the scientific method to sth. Traditionally, sth is "the world", but it's not too different if it's just another set of data.
> Plus, not a minus. I think the 13" MacBook Air is the best laptop on the market today. Tight integration between hardware and software is key. Sorry? How is a restriction a plus? Can you use a Lenovo with OS X? No.…
Makes it sound as if those things were mutually exclusive. They are not. I don't like the attitude of this article. Good soft skills will not compensate lack of smartness. This might not appear in a job interview…