javascript-algorithms VS Dlib

While browsing trending repositories on GitHub, I discovered trekhleb's javascript-algorithms repository. This repository focuses on helping new developers learn and implement algorithms, serving as an educational resource rather than a traditional software product. I find this approach appealing, as it aligns with my desire to contribute to projects that empower others to learn and grow.

3 . JavaScript Algorithms and Data Structures This repository contains JavaScript-based examples of many popular algorithms and data structures. Each algorithm and data structure has its own separate README with related explanations and links for further reading (including ones to YouTube videos).

JS Algorithms JS Algorithms and Data Structures entire documentation teaching ranges of or almost all the DSA required topics javascript-algorithms

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

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.