Description
Can you see how building Machine Learning algorithms in C++ will open up more career opportunities for you?If more professional companies are using C++, it stands to reason that there is going to be more of a demand for C++ programmers. If it is not based web app, the ones who use Python for their ML products partly fail. However, if you are working with hardware, C++ is a must! Because C++ is a compiled language that you can easily extract the binary files which the thing machine talks. But the main reason companies should probably use C++ is because of power of it! C++ is super fast and is a general-purpose programming language that supports both procedure and object-oriented programming making it very flexible. It is readily scalable. It may also be portable. C++ has numerous capabilities that other languages just lack. This is the reason why C++ code can be interfaced with using almost any major language. Given how many languages C++ has touched, if you are familiar with C++ you will probably notice C++-related features in new languages you learn. Does this course focus on algorithms, or math, or what?!?! Let's face this - the great majority of online ML courses use Python that is the interpreted programming language. They advise using pre-built algorithms rather performance-based ones. Although you could get rapid accomplishment as a result of this, in the long run it will hinder your capacity to comprehend ML structure using C++. Understanding the underlying algorithms is a prerequisite for comprehending how to use ML approaches. That's the goal of this course - I want you to comprehend the precise math and programming methods utilized in the most popular ML algorithms as well as the C++ programming language. Once you possess this information, you may quickly learn new methods and create far more fascinating projects and apps than other engineers who are simply familiar with how to provide data to a magic library. A short list of what you will learn to: Advance memory profiling to improve the performance of your algorithmsCreate applications using the robust current C++ STD librariesSet up a CMake projectCreate software that is compatible with Windows, Linux, and Mac OS X! Use C++ to write clear, understandable ML code without employing single-name variables or perplexing functions. Understand how to modify standard algorithms to match your own use casesStudy performance-boosting techniques that may be used with every C++ code typeTechniques for importing data and arranging using CMake
