Readit NewsAs all my computers run Linux these days, it also has replaced all my "from-x-to-android" transfer apps.
Pros: - Has plugins for anything.You're doing C++, just install C++ plugin and you're good to go. Want vim key bindings there's a plugin for that as well. I use a plugin that can scrape competitive coding websites and automatically create tests for a problem. - Git, snippets, etc all modern IDE features built-in. - It is also found on many websites as an editor.
Cons: - Since it's electron. System requirements are on the higher end.
A major issue that I've seen is that of most beginner-focused educational content not being fast enough to learn with for the more experienced developer. This along with the fact that time is often a big issue for us. I've had numerous times where I had to learn a new framework within a 1-2 week time span in order to plug some work gap or speed up a project, and found no legitimate resources that could allow an intermediate developer like me to learn faster.
This is why I am currently creating content targeted specifically at intermediate to advanced developers and teaching new languages and frameworks (using the 'constructivist' method) in a way that makes the process of learning them much more efficient. In short, faster.
It's a little rough around the edges but you can check out the blog where I share my current tutorials here: https://fromtoschool.com.
To gain a better understanding of why the method of teaching that I've described is more efficient than others for the intermediate developer, check out this post: https://fromtoschool.com/why-most-programming-tutorials-are-....
It's funny because when I saw that line I thought I would be pedantic and double check to see if you got the laplacian smoothing correct (because in practice it's never "that simple" for any numeric algorithm) and then realized that you don't understand how to implement Naive Bayes' at all.
For starters you aren't using probability. If you want to put all of the words in each document together into a two dictionaries of counts, then for each word in the unclassified document you want to look at the product of the probability of those words appearing in the spam corpus vs the non-spam corpus. That probability is n_word/total_words the corpus.
This is where you need to do some smoothing because if a word does not appear in the one of the corpora then you will get a probability of 0 for that class. Smoothing just adds 1 to the numerator and N_classes to the denominator. It is the equivalent of assuming a weakly informative uniform prior.
In this case, wouldn't it actually be better to just drop the denominator, because it will be the same for both (spam & not spam).
I appreciate the magnitude of cyberchefs operations, but having to switch to the browser for these tasks can be cumbersome at times.
[0] https://chepy.readthedocs.io/en/latest/
Edit: I had missed that cyberchef offers a node API exposing most of its operations: https://github.com/gchq/CyberChef/wiki/Node-API