javascript-algorithms VS Dlib

I'm reminded of the time when some kid wrote a script to crawl GitHub and create issues[1] about using inclusive language... except it was really dumb, for example: https://github.com/trekhleb/javascript-algorithms/pull/875/f...

[1] E.g.: https://github.com/EbookFoundation/free-programming-books/pu...

Try codewars or leetcode Or you can use this repo for ds practice https://github.com/trekhleb/javascript-algorithms

This one is pretty popular too.

for algos - not sure how much you'll need to do for a jr position but familiarity with some of the beginner stuff here couldn't hurt: https://github.com/trekhleb/javascript-algorithms

Traditionally, a linked list allows you to insert before/after a node. i.e. addBefore(node,value) (see [2] ) He doesn't implement addBefore & addAfter.

Instead, he provides a whole bunch of non-canonical helpers like reverse(), toArray(), deleteTail() etc - these are typical LC-Easy problems that don't belong inside the data structure.

My own introduction to these things was a C course called "Data Structures in C" in the traditional CS curriculum, and yes, you would have to malloc a new node, get back a pointer with a memory address, & the process of pointing the next pointer of the current node to this new node so that the memory address of the next value was explicitly "linked" to the current value and hence linked list etc...I guess much of that terminology is lost on the new generation in the absence of pointers & memory addresses.

The canonical exercise in those days was - Show that a linked list does not store objects in contiguous memory, unlike an array. So to solve this, you would traverse the list from the head node & print the actual addresses of the memory locations along the way, proving that the vals aren't stored contiguously. I wonder what that exercise would mean in JS land.

That said, yeah its a good starting point & I applaud the effort.

[1]https://github.com/trekhleb/javascript-algorithms/blob/maste...

You could also check out: 1. 30 seconds of code 2. JavaScript30 3. JavaScript Algorithms

dlib

The apparent gender estimates from photos are using dlib, and I really ought to get what I'm doing cleaned up in such a way that other people can use it easily.

I really like dlib's code https://github.com/davisking/dlib

Additionally, C++ may be used for extremely high levels of optimization even for cloud-based ML. Dlib and Kaldi are C++ libraries used as dependencies in Python codebases for computer vision and audio processing, for example. So if your application requires you to customize any functions similar to those libraries, then you'll need C++ knowhow.

If you know C++, you don't need anything else. Go and learn APIs for C++ libraries. If you're into DSP, why not study Dlib?.

The data is mostly in this spreadsheet. The apparently facial gender estimates are made with Dlib. The mental health assessments are from Beck's Depression Inventory and the Snaith-Hamilton Pleasure Scale. The graph is made with gnuplot.

The plugin uses dlib library with a very fast HOG detector for both face recognition and detector following the relative examples.

The dlib facial recognition model thinks that I am now a distance of about 0.3 from where I started, which is far enough to start getting many false positive matches, but still within the design intent that different pictures of the same individual will be within 0.6 of each other.

Dlib's face recognition module thinks that I am about 0.25 units away from where I started; its design intent is that distinct individuals will be 0.6 or more apart, although in practice other people start showing up around 0.3.