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I would look at languages like C++ and Python and their respective frameworks for computer vision and imaging.How is better to study computer vision development?
Yes and it is still used quite extensively. Driver still use pure C to an extent as well as embedded systems.It has pure C in it! Is there even an IDE for pure C?
How so? OOP isn't some magical answer to solve all programming problems. It's a paradigm which can be suitable in some situations and not suitable in others.Starting with a non-object-oriented programming language is a huge mistake anyway.
Again, how? You can simply compile the program for a different architecture and different operating system.C++ for game development is only practical on Windows.
These are very specialised languages which are used to solve a particular set of problems. Someone who has never programmed before will not need to know these immediately.It doesn't even mention data sciences. R, Julia, and F# fall in that area.
You just contributed one more item to the list of the infographic's flaws. What can I say? The author must have thought, "you wanna get started and learn, but you're not a kid? Oh, I know. Read the dragon book and develop device drivers! And forget that you can do that with C++/WinRT, Rust, Delphi, etc."Yes and it is still used quite extensively. Driver still use pure C to an extent as well as embedded systems.
OOP gained popularity and stayed popular because it was a great innovation. Not all paradigms are created equal.How so? OOP isn't some magical answer to solve all programming problems. It's a paradigm which can be suitable in some situations and not suitable in others.
I said impractical, not impossible. You can, if you know you'll live for 200 years, can spend 200 years on a video game, have nothing better to do with your 200 years, and most importantly, don't want to release your game for Android, iOS, and macOS.Again, how? You can simply compile the program for a different architecture and different operating system.
You are describing R alone. F# and Julia are general-purpose. Julia is Python's rival. But I can see that author of the infographic was a Python lover.These are very specialised languages which are used to solve a particular set of problems.
I know many university alumni who have never learned a programming language other than one of these.Someone who has never programmed before will not need to know these immediately
How is learning C a flaw? Almost every commonly used modern language derives from C in some aspect. C++ is C with classes added.You just contributed one more item to the list of the infographic's flaws. What can I say? The author must have thought, "you wanna get started and learn, but you're not a kid? Oh, I know. Read the dragon book and develop device drivers! And forget that you can do that with C++/WinRT, Rust, Delphi, etc."
I wasn't suggesting that OOP isn't a great innovation, but I believe many programmers fall into the trap of picking something because it's popular rather than because it's required. And I still disagree with the statement about one paradigm being better than the other. Look at C# now, it's taken what was good from so many other paradigms, hence it's popularity among professional developers.OOP gained popularity and stayed popular because it was a great innovation. Not all paradigms are created equal.
Desktop and mobile games have totally different interfaces and underlying architectures, you would probably need to develop a separate version if you had a complex game.and most importantly, don't want to release your game for Android, iOS, and macOS.
Then why state F# and Julia fall into that category then? It seemed that you were inferring that those languages should be used for data science only. I know that they can be used for problems other than data science, but it doesn't mean that they suitable for those other problem domains.You are describing R alone. F# and Julia are general-purpose.
They may have been; everyone has their biases. Python is a great beginner language and has some great libraries.But I can see that author of the infographic was a Python lover.
I know many university alumni who haven't; what's your point?I know many university alumni who have never learned a programming language other than one of these.
Good. (I know, you said a lot of other things, but I think they amount to "we disagree.")I wasn't suggesting that OOP isn't a great innovation
Exactly what I was saying. And exactly the opposite of what the diagram says. It mustn't mislead people interested in developing games for mobile devices to go that way. Or at least, the "3D/Gaming" label must read "3D/Gaming on PC". Even on PCs, you can create games with JavaScript + WebAssembly + WebGL.Desktop and mobile games have totally different interfaces and underlying architectures, you would probably need to develop a separate version if you had a complex game.
Exactly! So, can't you see the diagram's flaw? If not, let's take it from the top. The diagram in question starts by asking "Why do you want to learn programming?" One important branch omitted from this diagram is, "Make money → Get a job → Which platform/field → data sciences." There are several possibilities here: R, F#. Julia, and probably more.Then why state F# and Julia fall into that category then? It seemed that you were inferring that those languages should be used for data science only. I know that they can be used for problems other than data science, but it doesn't mean that they suitable for those other problem domains.
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