LMAOOOOOOOO! bruh

lol

Or is it?

I actually clicked on this video thinking that's Michael 😂

his name is actually michael 😂

Bro she was reading off a piece of paper 😂

Common theme in my observation over the past year. Look at the data science team of Wayfair for example. Neuroscience, biochemistry PhD's are now becoming Data scientists. If you think about it PhD guys have at least 3-4 stats heavy courses. But the ones who get calls have published 2-3 papers which have some large scale data analysis. The best way to get noticed is to do say 5 kaggle projects. Cover all areas like binary classification, imbalanced datasets, regression, CNN and lstm etc. Also, important to do some basic SQL like he said.

I@@apoozeo1715 If you want a really good job especially in today's climate, I think the answer is in your original answer, publish in top ML journals like at Neurips not just in Kaggle data science tournaments. The competition is changing.

actually machine learning is from academics top phd like that in the beginning, it just Andrew Ng that democratize and over-simplified the Machine Learning courses

this has always been the case

At least in my country (I live in Brazil and I'm graduating in physics) being a physicist that really researches is hard, especially now that the government ended most of the financial incentives for it. But politcs apart, the graduation is giving a lot of advanced math knowledge together with the concepts needed to solve problems. Generally is easier to have a more enjoyable life if I just follow another profession since almost any would benefit from what I'm learning.

So did I 😂 they look so much alike

true !!!

Yujiao Li i also got quite some disagreement when he thought "data learning" can replace exploratory work, wangling process thus feature engineering. Data science is a lot more about prediction, eventually insights are the derived value, which comes from beating the data

so if i want to be data analyst i must had good skill at statistic?

agree 100%!

Thanks for breaking things down. I get confused with all of this.

It looks like a smart watch to me. Samsung Gear maybe.

MONEY MONEY MONEY

Do they earn that much though?

You kidding me?? He wouldn't have gone for the PhD if he was THAT attracted to MONEY

@Intelligence Injection That is exactly what I am saying... If he wanted money, he would have gone to data science straight from undergrad not after doing a freaking PhD in Physics... It is really REALLY hard to get though a PhD and money is never a motivation for a PhD student

Didn't realize white folks were clout chasers, too.

he referring to web scraping. You can web scrap using python in a framework like ScraPy. But you can also use SQL to if you have direct sources of the data

Genius? He works for someone other than himself. See what "The TechLead" or "Jarvis" have to say about Google. He failed his first interview and i'll bet those people didn't have a PhD. Hell, he can't even score the chick sitting next to him. He just has focus. Definitely not distracted with chasing women or getting wasted with friends or watching sports. #facts

@@NuEnque wtf does trying to sleep with the interviewer have to do with anything? That statement shows how juvenile you are. The phrase "score the chick" also means you're probably 30+ still acting like that.

@@bc9273 Was that all you got out of my comment? Clearly I struck a nerve!

@@NuEnque your comment was ridiculous. You tried to insult him to make up for something you apparently lack. I would say that he clearly struck a nerve with you. As for you striking a nerve with me, I don't get bothered by grown men using insults made by children on an elementary playground. I probably shouldn't have made my original comment, though. People your age acting like that are never going to learn from anything or anyone and mature.

NuEnque you're truly obnoxious

And which approach turns out to be optimal?

@@prasadkadam4915 I think both are important. Id say an engineer is better at various tools and a scientist has more intuition and theoretical knowledge. Thats my opinion

@@prasadkadam4915 From experience, a scientist tends to do quite a considerable amount of research, and as such, does more theoretical work before getting his hands in the dough. Scientists' workflow tends, thus, to be considerably long until there is any valuable execution, with a promise of a very fine-tuned model upon completion. Engineers tend to first find something that works, regardless of how perfected it is, and then improve it in a somehow iterative way. Thus, this can take several things in consideration. Do you have the money to invest in such a long term project? Are you working on R&D or are you executing on a small time frame? Do you need the best model in the market, or a model that will get the job done? What is optimal depends in the company's resources and objectives.

That's deep learning I guess

Linear regression for regression pb and logistic regression for classification pb. So you can use both LR to solve most data science pbs.

@Jerome Dillon Yeah, ur ryt ! human.I will definitely follow up on your words just to see if leaving google is worth for me :)

The Master Algorithm is a good book for breadth if you are just starting or early in your career.

@@Urbrosfriends2ndcuz is it pedro domingos books????

Yeah, that's the one :)

my email is ganeshghimire40@gmail.com

archive.ics.uci.edu/ml/datasets/auto+mpg

@@CasternFernandes22592 👍

www.google.com/search?rlz=1C1GCEA_enIN833IN833&ei=mbt_XMGWD4200PEP_9-OkAg&q=uci+auto+mpg+dataset&oq=auto+mpg+uci+dataset&gs_l=psy-ab.3.0.0i22i30.635.3623..4456...0.0..0.599.6531.5-12......0....1..gws-wiz.......0i71j0i20i263j0.s-LtFG9jeao Click on the first link

@@CasternFernandes22592 Yep this is the one.

Yep! In programming, when we say memory, we generally mean RAM.

hi im undegraduate business student n really want to know more abg career of data analyst, can u recommend books or course that worth to learn??

Classify a data set with a rule or algorithm. Then, count the number of true positives. Count the number of false negatives. Divide the number of true positives by the sum of true positives and false negatives. That's recall! More intuitively, recall gives tells you what fraction of positives in a dataset your model can correctly identify.

en.wikipedia.org/wiki/Precision_and_recall

Sequel

Yes

Static(?) Query Language

Lazy programmer cliche

Nah, it wasn't useless at all. My graduate studies built the technical foundation that has served me throughout my industry. It's not necessary to go to graduate school for science to switch to DS - it's just the path I took after completing my graduate studies and deciding to head for industry. We're all collections of experiences and influences - it's hard to underline something I did, and then say "yo, go do this". The things that helped me were learning to program, learning how to work with large data sets, tell stories with data, math and statistics. I basically didn't know any "ML" when I started my journey - that was all picked up on the job.

Wow!

Did you switch?

I feel you ,The job prospect in academia is really bad and it's hard to get a tenure nowaday. :(

yes it is but it helps to have more experience & solid background in theory!

most data scientist are not PhDs! I have never been in industry (have a PhD in math), but that's what I get from Andrew Ng's speeches. PhDs (research scientist/ applied scientist. whatever the title may be!) usually do the research/problem solving/ and hand it down. It does not not seem the data science wave will be dampened for awhile, but I want the hotness and career opportunities decrease so I see what people will be "passionate" about!!!

@@applewatch4085 hi im undergraduate business student n really want to have more study abt data analyst, can u recommend me kind of books or courses that worth to learn????

@@melaniaadelia9387 "The Elements of Statistical Learning" is very well known book, whose authors are among the top two teachers/explainers I have ever seen. It is freely available on their website. You may find it hard to follow, but good thing about it is that at the end of each chapter it has bibliography. So, you would be on the right track. UW machine learning course on Coursera is good start. For deep learning, Andrew Ng just gives big picture, you can look at "CS231n" on youtube, this is better than Andrew. Also, what follows should have been mentioned first: depends on what you want to do. research? or not Recommender system?, autonomous driving, etc. Perhaps you should talk to faculties at Stanford or UW who are on the cutting edge of science and also work for industry, and some data scientists in industries like Google Amazon, etc. Lots of them may not respond, it (talking to people, especially in this field, according to my experience) is a low-output process that you have to do, the sooner the better. Also, you can start working on Kaggle projects, real practice is really really important, and will instill the knowledge you learn in you! You will see problems that are not in the books which are vanilla. Let the problem lead you what is needed to learn. I, myself, am stuck behind the industry doors, however, I hope it was helpful!

@@applewatch4085 thankyou very much, hope ur career always going well. God bless u😊

Actually this is something that is going around my head for a while,clearly you need to be good at maths(basic + advanced) and statistics to be a data scientist.I have seen courses that don't have maths and they just teach tools and stuffs,sure tools help, but sometimes you need to develop your own sets of formulas to solve a certain problems with respect to data science.

@@MegaRockandroll09 hi im undergraduate business student n really want to have more study abt data analyst, can u recommend me kind of books or courses that worth to learn????

@@melaniaadelia9387 , you need to know basic statistics and some some basic mathematics,for books you get books on platform(like R or python) which shows you how you can apply those maths functions to get the desired output.

@@MegaRockandroll09 Bro, I too am a theoretical physics enthusiast, pursuing a dual degree from IIT Madras in Data Science and programming. What about you??

Michael Toblerone

use google :) i easily find him in 10secs

Michael Beaumier

@@amandamate9117 first you said his name is bald testestorne junior and then changed to beaumier ? :D

BRENT KASKEL

use google :D it is ez it took me 15secs to find him xD

@@username42 thanks.

@@nitishjoshi9456 no problem

Michael Beaumier

@@amandamate9117 this ☝

Honestly you do not at all need a PHD to be a data scientist, though it is impressive. Some people get into the industry with much less; this man's qualifications are beyond the job's demands. Consider also that this is google rather than a standard company; they are a lot more selective and are not the standard for most.

I guess you can only thing about yourself. As a physic student it is quite useful to know your future job paths.

Because it's an accomplishment he earned? He left a great field for data science, that's kind of important to know. Your jealousy is showing.

did you have a stroke? are you ok?

What a sad thought :(

Go with Python it will be undergoing different Job fields like Big Data, Data Science, Web Technologies, and AI.

If you’re asking to choose between the two you haven’t come across the right project that’ll force you to use both heavily, SQL --> Python for post process.

They are two different technologies completely if you are doing data science at all you will need python. for building models , pre-processing, data wrangling all of the above. SQL will just be used if you have your data not stored in memory, I work as a data scientist and use python and R every day. 80% python. I learned some SQL while studying but have quite literally never used it in work

@@MrPauricg i have questions,Do you need to be good at maths to be a data scientist??

@@MrPauricg so what the things that always important as data analyst or business intelegent, im undergraduate mba n really want to be data analyst

I feel the last one

Apple Watch gotta find some deep-sounding reason, though.

he did say it but in coded language "good career opportunity"

Can you really blame anyone for leaving academia

Yes! And why does the interviewer have a better one than the interviewee?

I’m from Google and I like it :) Very insightful and spot-on. (My personal opinion, not representing Google.)