javascript-algorithms VS tech-interview-handbook

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...

We are currently following the tech interview handbook , currently on arrays and practicing sliding window technique.

Tech Interview Handbook is another resource that would be helpful.

As per title, I am looking out for good interview resources for machine learning engineer. In software side, I have heard of https://www.techinterviewhandbook.org/ to be one of the best.

Technical Interview Guide for Busy Engineers | Tech Interview Handbook