I recently graduated as data scientist & software development, and this video sums it all up. I enjoyed watching it Thank you So much
@julesmules09012 жыл бұрын
This is superb and we sure need more of your content! Really, really good job - Kudos!
@yu-chenlin95384 жыл бұрын
A very easy understanding visualization that helps any layman like me to understand the complex concept of data science and machine learning.
@hovermind Жыл бұрын
I am Azure Solution Architect, now I am interested to become a Data Architect 😊
@AltexSoft Жыл бұрын
Wish you luck, if you'll really ever try it)
@jseebohm29 ай бұрын
Your videos are amazing, I've been looking for a channel like this
@ilhantanriverdi4 жыл бұрын
Very well explained in a simple and visual way. Thanks!
@GustavoStork4 жыл бұрын
Thank you so much. That was so helpful. I started creating a data science team in my job.
@SGUKProcess2 жыл бұрын
Great video - I've done most of those jobs over the last 10 years. But you missed out Data Artist! Analysts are fantastic with numbers but often lack the User Experience skills that are supplied by a Data Artist.
@kiwi-mf2do Жыл бұрын
I want to get into this field but that last line of this video bothers me. Will we really become redundant?
@chesslife23453 жыл бұрын
im studying machine learning and data science since pandemic begin.. and start to build my own system to seek opportunity in business, jobs etc. do you think i can make it own my own and got only associate degree in computer science. but i love what im doing and im excited to have the result of my work even it takes years.
@JaimeLessains11 ай бұрын
IMO, Netflix's explanation is BS. In reality, removing the percentage rating is to provide the users less information about the content. This in turn pushes the customer to actually try that movie/show to see if they like it. On the other hand, with percentage rating, the customer will naturally avoid what they consider low rating, just like shopping on Amazon -- so in the whole, less viewing by the user.
@brayanrai28802 ай бұрын
This video made me subscribe this channel, Thanks it was amazing video
@albertosei3558 Жыл бұрын
Great video. You broke it down very well. Thank you
@chieziearthurezenwaegbu4639 Жыл бұрын
Powerfully captured 👍
@shraddhapatil9263 жыл бұрын
Love all your videos related to data. Got a little worried when the last part mentioned that Data Scientist/BI work will be taken for granted and that it will become common to functionality in any given software. Does that mean that this role has limitations expanding to the future? Once all the models are trained and automated to be consumed , what next?
@itskayallday3 жыл бұрын
I think they mean that it will stop becoming exciting and futuristic, and more something part of normality - don't worry too much :)
@AShina-zn7nx2 жыл бұрын
Overtime Career Pathways or the Career itself will soon become overrated, that was what the narrator means by the last part. We have started seeing few examples in Data Workspace, Visual Recommendations (based on the labelled dataset) ....... which greatly reduces analyst interference to analyse and communicate data by visualization. Going Forward, it's best to start incorporating Data Automations, Advance Data Engineering or Pipelining and APIs to ........ design workable system without Humans interference
@kiwi-mf2do Жыл бұрын
@@AShina-zn7nx Thanks for the reply.
@rubermanrodriguez56354 жыл бұрын
Very insightful
@Floflox2 жыл бұрын
juste perfect
@wllzak98182 ай бұрын
Thanks it was amazing video ☺
@panTadzik Жыл бұрын
Great video!
@onong39194 жыл бұрын
Thanks for the video.
@tsunamio775010 ай бұрын
0:26 Netflix removed ratings because a left leaning comedian, Amy Schumer, was getting downvoted to hell and created cracks on which opponents of wokness could climb the wall to freedom. The old rating made the difference between awesome movies people would actually paid for and sub-standard movies people watched "for free", due to the subscription system.
@fernandog97933 жыл бұрын
Greate video! Thanks :)
@azzabenabid26692 жыл бұрын
i love this video
@markybolton8 ай бұрын
good video
@sanjaybarnes57172 жыл бұрын
The video said Data science will die down because of automation. For quite some time now I have been saying I do not want to apply for a position as a data scientist. I want to apply as something else and use my data science skill. Why? Because of the same automation reason. You have to think ahead of all industries. Also, I do think the world will be in trouble if the governments allow companies to automate everything and a lot of thing. Jobs will be taken away and this can obviously cause economical and social issues. I think every business owner big or small should learn circulatory economic and how there actions affect municipalities, towns, cities, states, and the country.
@AltexSoft2 жыл бұрын
We didn’t say that data science will die per se. It’s likely that DS will become one of the branches of software engineering. As for automation, it’s completely normal and has always been around. And it’s not likely that automation will cause unemployment in the future. Automation normally doesn’t take over entire jobs. Instead, it takes over specific parts of a job structure, kind of like a calculator makes an abacus obsolete but doesn’t force an accountant to the street. Well, unless your job structure consists of a couple of simple operations. Once some part of the job structure becomes automated, people can focus on the rest of their responsibilities and learn new skills. We have an old article breaking down this matter. Give it a look if you’re worried. www.altexsoft.com/blog/business/reality-check-robots-are-here-to-automate-your-job-or-not/
@lordk12 Жыл бұрын
jobs are not taken by automation, they are only replaced by other kind of jobs, usually more specialized (meaning, better paid). Automation improves efficiency, and that results in greater profits for the companies. This allows better economical and social conditions, and higher average living standars.
@14xx072 жыл бұрын
Statistics is definitely easier to learn than the unending load of programming to learn.. Data scientists are basically leaching off of other experts with hard skills.