Python dependency management of packages using C or C++ behind the scenes is really problematic and sometimes, the installation may fail. In this case, a solution is to use Conda or mini conda which provide many pre-compiled packages and also Clang C++ compiler.
An alternative way to allow people without software engineering background to play with Python data science and machine learning tool may be providing pre built Docker images with everything pre-installed which may save one from configuration trouble.
Docker is also useful for learning about new programming languages without installing anything. With just one command $ docker "run --rm -it julia-image", one can get a Docker image containing a GOLang compiler; a Julia language installation; a Rust development environment and everything else. Docker is really a wonderful tool.
An alternative way to allow people without software engineering background to play with Python data science and machine learning tool may be providing pre built Docker images with everything pre-installed which may save one from configuration trouble.
Docker is also useful for learning about new programming languages without installing anything. With just one command $ docker "run --rm -it julia-image", one can get a Docker image containing a GOLang compiler; a Julia language installation; a Rust development environment and everything else. Docker is really a wonderful tool.