Lads, I will be real with you: some of you show absolute contempt to the actual academic study of the field.

In a previous rant from another ranter it was thrown up and about the question for finding a binary search implementation.

Asking a senior in the field of software engineering and computer science such question should be a simple answer, specifically depending on the type of job application in question. Specially if you are applying as a SENIOR.

I am tired of this strange self-learner mentality that those that have a degree or a deep grasp of these fundamental concepts are somewhat beneath you because you learned to push out a website using the New Boston tutorials on youtube. FOR every field THAT MATTERS a license or degree is hold in high regards.
"Oh I didn't go to school, shit is for suckers, but I learned how to chop people up and kinda fix it from some tutorials on youtube" <---- try that for a medical position.

"Nah it's cool, I can fix your breaks, learned how to do it by reading blogs on the internet" <--- maintenance shop

"Sure can write the controller processing code for that boing plane! Just got done with a low level tutorial on some websites! what can go wrong!"

(The same goes for military devices which in the past have actually killed mfkers in the U.S)

Just recently a series of people were sent to jail because of a bug in software. Industries NEED to make sure a mfker has aaaall of the bells and whistles needed for running and creating software.

During my masters degree, it fucking FASCINATED me how many mfkers were absolutely completely NEW to the concept of testing code, some of them with years in the field.

And I know what you are thinking "fuck you, I am fucking awesome" <--- I AM SURE YOU BLOODY WELL ARE but we live in a planet with billions of people and millions of them have fallen through the cracks into software related positions as well as complete degrees, the degree at LEAST has a SPECTACULAR barrier of entry during that intro to Algos and DS that a lot of bitches fail.

NOTE: NOT knowing the ABSTRACTIONS over the tools that we use WILL eventually bite you in the ASS because you do not fucking KNOW how these are implemented internally.

Why do you think compiler designers, kernel designers and embedded developers make the BANK they made? Because they don't know memory efficient ways of deploying a product with minimal overhead without proper data structures and algorithmic thinking? NOT EVERYTHING IS SHITTY WEB DEVELOPMENT

SO, if a mfker talks shit about a so called SENIOR for not knowing that the first mamase mamasa bloody simple as shit algorithm THROWN at you in the first 10 pages of an algo and ds book, then y'all should be offended at the mkfer saying that he is a SENIOR, because these SENIORS are the same mfkers that try to at one point in time teach other people.
These SENIORS are the same mfkers that left me a FUCKING HORRIBLE AND USELESS MESS OF SPAGHETTI CODE

Specially to most PHP developers (my main area) y'all would have been well motherfucking served in learning how not to forLoop the fuck out of tables consisting of over 50k interconnected records, WHAT THE FUCK

"LeaRniNG tHiS iS noT neeDed!!" yes IT fucking IS

being able to code a binary search (in that example) from scratch lets me know fucking EXACTLY how well your thought process is when facing a hard challenge, knowing the basemotherfucking case of a LinkedList will damn well make you understand WHAT is going on with your abstractions as to not fucking violate memory constraints, this-shit-is-important.

So, will your royal majesties at least for the sake of completeness look into a couple of very well made youtube or book tutorials concerning the topic?

You can code an entire website, fine as shit, you will get tested by my ass in terms of security and best practices, run these questions now, and it very motherfucking well be as efficient as I think it should be(I HIRE, NOT YOU, or your fucking blog posts concerning how much MY degree was not needed, oh and btw, MY degree is what made sure I was able to make SUCH decissions)

This will make a loooooooot of mfkers salty, don't worry, I will still accept you as an interview candidate, but if you think you are good enough without a degree, or better than me (has happened, told that to my face by a candidate) then get fucking ready to receive a question concerning: BASIC FUCKING COMPUTER SCIENCE TOPICS

* gays away into the night

Look what I found!
Even my L3 cache is bigger than this!

“Those were the days😂”

Code never lies
Comments sometimes do

Nah!
Code lies too, especially when you train a neural network 😂😂

zero motivation for anything, i just want sit outside in the sun at the lake with ice cream and not in front of a screen. And not being bothered by the new vacum cleaner loud deep learning rig of the data science department in this open floor office.
I fucking forgot my noise cancling headphones. FML

The joy of a complete trained model.
Onto the next task. Use the model to automatically infer handwritten figures on a bankers check/cheque.

Switching to macOS was an entry to paradise.

I go to Windows only to play Call of Duty. It’s crap and always will be.

P.S no comments on Linux.

INTERVIEW. It tells everything about the company. I recently applied for a "big" company for the position of ML Engineer. The Job description was like "someone with good knowledge of visual recognition, deep learning, advanced ML stuff, etc." I thought great, I might be a good fit. A guy called me the next day. Introduced himself as a manager of the Data Science team with 8+ years of experience. Started the talk saying "it is just an informal intro". But things escalated very quickly. Started shooting Data Science questions. He was asking questions in a very bookish way. Tells me to recite formulas (like big formulas). When I explained to him a concept, he was not understanding anything. Wanted a very bookish answer. I quickly realized I know more about ML stuff than him (not a big deal) and he is arrogant as fuck (not accepting my answers). Plus, he has no knowledge about Deep Learning. At the very end, he tells me "man, you need to clear up your fundamentals". WTH??? My fundamentals. Okay, I am not Einstein or Hinton, but I know I was answering things correctly. I have read books and research papers and blogs and all. When I don't know about things, I tell straight away. I don't cook answers. So the "interview" ended. I searched that man on LinkedIn. Got to know he teaches college students Data Science and ML. For a fee of 50,000 INR. It's a big amount!! Considering the things he teaches. You can find the same stuff (with far higher quality) free of cost (on Coursera, Udacity, YouTube, free books, what not). He is a cheater. He is making fool of college students. That is why I sometimes hate "experience". 8+ years of exp and he is such an a**hole!! BTW, I thanked God for saving me from that company. Can't imagine such an arrogant boss.

TLDR: Be vigilant during interviews. It tells a lot about the company.

Come to a weekly deep learning meet up this morning 8.30AM. The event start at 10 AM.  While waiting I read news and play some game. As time near 10 o'clock I had strange feeling: The guest room so quiet, just me and 2 security guy.

Okay I think comittee that run this event a bit late because of traffc jam and I wait more. In the end the committee didn’t even show until 10.30AM. Later I found on another data science group today's event is postponed and I go home.

WHY DIDNT YOU GUYS MAKE ANNOUNCEMENT ON SLACK? YOU WASTE MY TIME WAITING 2 HOURS

We have been at a university of applied sciences today with our class.
It was kind of ok. I did expect more surprising things there. The whole building was smaller than our college (not the same as in the US). The rooms, where profs tell you things with a series of rows of seats, were dirty and pretty much used to the point that the seats are about to break easily.
I was expecting the university to be kind of the same as the universities you see in the movies lol.
It could have at least been bigger than our college and more "modern" than our school.
[...]
Anyways, let us get to the point here.
We were first in the foyer and afterwards in their main lecture hall.
We were introduced to the day's plans by a team of engaged students from different study programs and the president of the professors. Yada yada yada.
We got the full program in each room and each individual time span filled with study programs on a sheet of paper.
I did select pharmacy, media production, architecture, data science, applied computer science, computer engineering, mechanical engineering and future energies.
Pharmacy and data science were the most interesting study programs to me. I have asked one of the professors if deep learning was a topic for bachelor students, as well.
He said that that is only the usual case for people who got a promotion.
As an example he told me that yesterday he was at a conference hall with 10.000 people in which he gave a talk about deep learning. "Most of them were professors" he said. "Since this study program is new, it might change in a few years" he added to his conversation.

It is quite hard having to decide now.
Geo informatics and Aerospace Engineering did sound interesting, too.
There are a lot of things I would like to study at the same time haha.

Idk if I should just pick mechanical engineering first and add one or two after it to it. But that would take a lot of time. Geez.

The gap of data science in industry and academia is so large. As a data scientist in a large financial company, I see that people are still using traditional models such as linear regression and SVM, while people in academia keep inventing new concepts and techniques such as deep learning.

I am not saying that we should completely embrace deep learning, or stick to classic methods. But I just feel so surprised that the gap is so large...Sometimes I am even thinking whether I am doing the right "data science"...

When professors rely on YouTube to teach you the syllabus, you know this is our education system **

#India

I was always somewhere in the range of not athletic enough to be a jock and not smart enough to be a geek during high school so it left me in a fun little purgatory between social groups. Ever since I was a kid though I saw my cousin make flash games for fun and thats where my interest in programming started but I never really did anything with it.

It wasn’t until I broke a bone during a football game and couldn’t play or workout for 8 months that I started jumping head first into programming and IT WENT DEEP. After tearing through and intro to java book I started reading and watching courses about data structures and learning how to make mediocre apps and games. It was terrible as any beginner usually is but god was it fun.

Then college came around and I decided to major in computer science, got myself a nice starting job at a typical big tech company with an actually decent team to work with and I still have the same love for it all since I started with it.

“Train like a GAN!”

Deep learning and data science

There is fun in using Google Colab.

They unveiled free TPUs on Colab.
It took me an hour of really slow training to realise that even if TPU is enabled, you have to code it explicitly to enable it.
After an hour I realised I was using only the CPU 😂😂

**crickets in the background**