hgoury
This gradient descent visualizer is made with it for example [1] to interpolate the points when the prediction line moves.
[0] https://www.jasonhickel.org/blog/2019/3/17/two-hump-world
Indeed, let's not forget LibreOffice
I've also heard good things about Probabilistic Programming and Bayesian methods [1] by Cam Davidson Pilon.
[1] https://camdavidsonpilon.github.io/Probabilistic-Programming...
The military branch of the PYD party was crucial during the fight against ISIS. Leaving them to die in Erdogan's hands is tragic.
In my opinion, there are a few points that are dubious in this analysis:
- A country is not like a person. It doesn't make any sense to compare the situation of a state to that of an individual.
- Different countries are engaged in trade together. If one, say Germany, has commercial surplus, it is because others buy its production. Hence, all countries can't produce like Germany : who is going to buy everything?
- According to mainstream economic doctrine (Keynes), cutting government spendings does not lead to growth especially amidst a crisis, whereas you have an alternative that does create growth and does not condemn people to starvation. This is done instead by increasing the spendings in the right way.
- Various officials have falsified economic documents in order for Greece to enter the Eurozone (and was helped by Goldman Sachs [0], for example). Why should people suffer from acts of this nature ?
[0] https://www.independent.co.uk/news/world/europe/greek-debt-c...
I haven't used rope extensively, it's too bad that it doesn't work well. It's open source so I guess it needs more contributions.
Note that a new extension, that works alongside the original python extension, has been developed by Microsoft: Pylance. It speeds things up based on pyright, a python type-checker.
For refactoring you can use rope [0] as a VSCode extension.
Sadly, looking at the github repo it seems to be unmaintened, so I am glad to see Muze in that space.
[1] https://github.com/vega/voyager
There is also Cox's theorem, that essentially states that probability theory is the only sound system that extends logic in the presence of uncertainty, to continuous values (between 0 and 1) instead of the two values 0 and 1.
With the same definition, switching A and B roles, we have p(A, B) = p(B|A) p(A) (2)
Plug (2) into (1) and you have Bayes rule.
I am a happy owner of a Microsoft Sculpt keyboard and mouse, and it is quite mobile. It has a built-in wrist rest as well.
It looks promising for these kinds of daunting tasks
It is very powerful, uses special files stdin/stdout when file argument is "-", supports groups, subcommands...
- Inputs are the things employees can act on easily, like the number of LoC written or the number of features developped.
- Outputs are related to business success, for example the number of customers, or the revenue.
The key here is to consider the external business environment as a complex machine, in which you put some effort, measured by inputs, and you observe the outputs as a result (reward). Because you don't know how the environment is going to respond, running the activity consists in adjusting the measures of inputs according to previous results, and trying to maximize those.
This is sane for business because executives can focus on maximizing the input metrics, without caring too much about the outputs, and evaluate separately the assumptions they made about the business (e.g. that x number of features requested by customers developped within 1 month increase the userbase).
It kind of looks like a reinforcement learning process actually.
Since it was a very powerful tool but struggled getting traction, they are using it as the core query tool for power BI (alongside DAX for great dashboarding).
Well done Microsoft.