leblancfg

The content of the challenges aren't the focus. The main take-away is to see how Norvig does it after you've had a whack at it yourself. You can learn a lot by seeing how he reads the problem, dissects it into different functions, documents and tests them, and keeps an eye out for performance and computational complexity.

His code is highly readable and elegant, and I wish every single person I'll share a codebase with will have studied him before.

There's a video (now pay-walled) from Cameron Davidson Pilon of Bayesian Methods for Hackers fame, where he takes this approach to build a basic Markov Chain model to predict patterns in his browsing.

https://dataorigami.net/collections/all/products/create-mark...

As the OP is writing Python, they are probably using a tool called Sphinx, that formats a codebase's docstrings (inline comments for functions, classes and methods) into reST, html, and many others. A total life changer.

There wasn't a single line of Clojure in that hour-long talk, I don't get your point. Do consume the content before you comment on it.

I've regularly heard good things of Olin College in the past years, especially when it comes to teaching CS early to all engineering students. Was not surprised to read this headline, but have never met any grads personally.

Lovely stuff! Any working examples / demos of this anywhere on the web?

For most messaging in larger organisations, having "paper trail"-style replies that you can forward to others has its advantages -- it better delimits in a single page who said what, and when.

If I know my conversation is intended to a small group I'll reply inline, but my default is quote-on-top.

"As someone who slightly prefers tabs" ... "I generally prefer tabs"

wat

That's amazing, thanks so much. Ernie, if you're reading this, great job :)

Thanks dehhn. From the LRO picture in the article, you can see that they're actually taking high-precision elevation maps of both the Moon and Earth into consideration, which sounds like something rather computationally intensive. I might be wrong, but I don't think they used Blender to handle that.

I would be curious to hear what tool they actually use, their pipeline, etc.

Would love to hear how they generated the shadow contours from the Moon to the Earth's surface!

It would provide a fast, grid-like interpolation for any 2D data: think geospatial, GIS, etc. If I understand correctly, could also be used recursively to provide a lazy (but inefficient) way to calculate locations to an arbitrary precision.

Funny, was looking at this repo a few weks ago, which has got some usable code, and using the same dataset.

https://github.com/aqibsaeed/Estimation-of-Remaining-Useful-...

Related, please share if you have a probabilistic programming approach to this, à la Stan or PyMC.

This resonates well with my experience. In sports training, many top athletes will use 2-3 month cycles broken in 3-4 sections that focus on specific adaptations. Endurance, strength, power, etc.

For long-term goals, the most important section -- base conditioning -- aims at slowly building up your body's training capacity. If your body can withstand one more hour of workout without injury or sickness, then over time these gains will accumulate. As opposed to strength training though, it can take many months before there is a tangible difference.

I feel as though for the brain, and creative work in general, the situation is very similar. With months and years of "training", it too can withstand to work for longer hours. The parent's comment on creating the proper environment is certainly key.

Interesting, and I see it's backed by Y Combinator, too. Would need to see a price comparison with AWS and GCP, though. Do share if anyone does a proper write-up.

I don't think it's fair to ask of a stranger to take the time to fix someone else's cheat cheat if he's never going to use it. The criticism still holds, however.

If you want real feedback, take away every mention of YOU and the company from the home page. Rewrite it from the perspective of your potential first 100 users. Show them exactly what pipecourse is doing that they can't find on some other site.

I would be really grateful if someone could provide a paragraph or two as to how this would be understood in terms of the Bohmian interpretation.

I agree 100% with this. The 'disagree' part should at least come with some form of strings attached. Something like 'we need to be able to pull the plug early with this', 'you start with a limited budget', or similar. Otherwise it's useless to mention the fact that you disagree.

I expect a self-aggrandizing blog post on it any day now.

For my (and I imagine many among us) use case, this is the takeaway:

PyPy2 can now import and run many C-extension packages, among the most notable are Numpy, Cython, and Pandas. Performance may be slower than CPython, especially for frequently-called short C functions. Please let us know if your use case is slow, we have ideas how to make things faster but need real-world examples (not micro-benchmarks) of problematic code.

Tried this for quite some time now. The one part I find 100x more natural to do with the mouse is handling files and folders.

There's nothing quite like visually doing those things, and no worthwhile shell practice can quite compare.

Does anyone know if the opposite exists? That is, I have hundreds of semi-structured handwritten pages which I'd like to scan or photograph, and get decent text files out of.

Both serve a similar purpose, but are not exactly equivalent. I use Org to take notes and write prose. I guess Jupiter could be extended enough to support many features that Org provides...

I guess it boils down to having a hierarchical vs sequential document as the base form, really.

There's also MobileOrg on iOS, but can only read from WebDAV or Dropbox.

Interesting, though, as they never needed to own that platform to mine it for hiring leads.

I think you hit the nail straight on the head. Sure, Tensorflow will also probably get pushed in the form of tutorials, etc. but I certainly think it's rather related to bring a way to popularize GCS.

Just to play devil's advocate here, in many cases the reasons stated for refusal are only one part of it.

In his case, the author doesn't seem to have had an offer on the table. Perhaps the interviewer felt as though the candidate was trying to negotiate too much, too early in the process. Perhaps the interview didn't go over all that well?

Sorry, I still disagree with that comment. They're not comparing apples and oranges, here, they're saying "here's why we're using apples to approximate oranges". The graph is showing a close linear relationship between # of cars and stock price.

It's saying "There is some a and b such that:

    a * "number of cars" + b ~ "stock price"

You can have a gripe with that method, sure, but the graph is fine.

Really does sound like "Let me shame your practices by redefining what this means in order to sell this service."