What does python artificial intelligence mean?

Python artificial intelligence refers to the realization of artificial intelligence based on the Python platform. Python is a widely used scripting language, and artificial intelligence is a new technical science that studies and develops theories, methods, technologies and application systems for simulating, extending and expanding human intelligence.

#Python is a very widely used scripting language. Google's web pages are written in Python. Python has demonstrated powerful functions in many fields such as biological information, statistics, web page production, and computing.

Artificial Intelligence (Artificial Intelligence), the English abbreviation is AI. It is a new technical science that studies and develops theories, methods, technologies and application systems for simulating, extending and expanding human intelligence. Artificial intelligence can simulate the information process of human consciousness and thinking. Python can be applied in the field of artificial intelligence, but Python alone cannot replace artificial intelligence.

The relationship between artificial intelligence and Python

The origin of artificial intelligence and Python lies in. Just like when we collect statistics or choose to use Excel to create tables, because when we need to use addition, subtraction, multiplication, division or functions, etc., we only need to apply the company. Because behind the operation of functions such as SUM and AVERAGE, the code has been written in languages such as C/C#, so Excel is only a tool and presentation form and does not perform calculations. Similarly, when learning artificial intelligence, Python is only a tool used to operate the deep learning framework. The main module responsible for actual calculations does not rely on Python. What really works is a lot of complex C/CUDA programs.

When deep learning artificial intelligence, the calculations are too complicated and they have to write C code to operate. At this time, programmers want to directly build the neural network, fill in the parameters, and not create a complicated Excel configuration table. Import the data and start training the model and get the results directly with the click of a button. This method is simple and practical, but the neural network is too complicated to build, there are too many parameters that need to be filled in, and the various options make it difficult to make it an intuitive graphical tool. You can only use a relatively easy-to-use language like Python to build a neural network, fill in parameters, import data, and call execution functions for training through simplified program code. Use this language to describe the model, transfer parameters, convert the input data, and then throw it into a complex deep learning framework for calculation. So why choose Python?

Scientists have long been fond of using Python to experiment with algorithms, and are also good at using numpy for scientific calculations and pyplot for drawing data graphs. It happens that Python is used a lot internally at Google, so it is inevitable to use Python. In addition to Python, the TensorFlow framework actually also supports JavaScript, c, Java, GO, and other languages. Ordinarily, artificial intelligence algorithms can also use these. But the official said that languages other than Python do not necessarily promise API stability. So artificial intelligence and Python are inseparable.

Speaking of the core algorithm of artificial intelligence, it is completely dependent on C/C. Because it is computationally intensive, it requires very fine optimization and interfaces such as GPU and dedicated hardware. These are all Only C/C can do this. So in a sense, C/C is actually the most important language in the field of artificial intelligence. Python is the API binding of these libraries. To develop a cross-language interface from other languages to C/C, Python is the easiest. It is much lower than the ffi threshold of other languages. CPython's C API is bidirectionally integrated and can be directly Exposing encapsulated Python objects to the outside world also allows users to introduce new features by inheriting these custom objects, and even call Python functions from C code.

Python has always been an important tool for scientific computing and data analysis. Python is the API binding of these libraries. To develop a cross-language interface from other languages to C/C, Python is the easiest, compared to other languages. The threshold of ffi is much lower. CPython's C API is bidirectionally integrated. It can directly expose encapsulated Python objects to the outside world. It also allows users to introduce new features by inheriting these custom objects, and can even call them from C code. Python functions. It is said that times make heroes. It can also be said that artificial intelligence and Python achieve each other. Artificial intelligence algorithms promote the development of Python, and Python also makes algorithms simpler.

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