Python as a programming language, its charm and influence has far exceeded C#, C++ and other programming language predecessors, programmers praised as the “most beautiful” programming language. From the cloud, to the client, to the Internet of Things terminal, to now artificial intelligence, Python applications are everywhere.
Two, Python is an interpreted language and writing programs is very important for people who do machine learning. Because you often need to make all sorts of changes to the model, which in a compiled language might be a one-off, Python can usually do it in a fraction of the time. For example, to write a matrix multiplication in a compiled language such as C, you need to allocate the memory for the operands, allocate the memory for the results, manually call GEMm on the BLAS interface, and finally reclaim the memory space manually if smart Pointer is not used.
Many C/C++ oriented libraries now support managed memory management, which makes the development process much easier, but interpreted languages still have the inherent advantage of requiring no compile time. This is very beneficial to the efficiency of machine learning, which requires a lot of prototyping and iteration.
The flexible syntax of Python also makes it easy and efficient to implement practical functions such as text manipulation, list/ dictComprehension, etc. It is even more convenient to use with lambda. This is one of the reasons behind Python’s healthy ecology. Lua, by contrast, is an interpreted language and even has the support of LuaJIT, but it’s hard to do what Python does, both because of its market share and because of its anti-common sense design. But with the Lua-Python Bridge and Torch, Lua seems to be parasitising.
In the next decade, the development prospect of Python language is promising. There is no doubt that more and more enterprises will use Python language, and the talent gap of Python programmers will be bigger and bigger. Python full stack development engineer, Python development engineer, automation development engineer, Linux operation and maintenance engineer, Python crawler development engineer, front-end development engineer, big data analysis and other popular positions.