Your perfect guide to understand the role of Python in Artificial Intelligence (AI)
Python has been a very important part of Google since the beginning, and remains so as the system grows and evolves. Today dozens of Google engineers use Python, and there is demand for more people with skills in this language. In the field of Artificial Intelligence (AI) the advancements are growing at an exponential rate. The demand for AI is at top level as there are innumerable transformations that are happening in this rapidly-growing technology.
Python is a high-level programming language used for complicated scenarios. It doesn’t require to be compiled into machine language instruction for execution. A developer It can be used to directly run the program.
This article on Artificial Intelligence with Python will give a comprehensive guidance on the concepts of AI with real-world applications and use cases in Python.
Python is one of the most popular programming languages used for AI by several developers. Guido Van Rossum created it in the year 1991 and ever since its commencement it has been among the most largely used languages along with C, Java, etc.
Python is relatively helpful by its prototyping algorithm for AI. Python has unique standardized algorithms that include intuitive syntax, data structures and basic control flow for AI and also is eased by interpretive run- time without standard compiler languages.
Python libraries for AI Tensorflow:
AIMA
pyDatalog
NumPy
Theano
Keras
SimpleAI
EasyAI
Python libraries for Artificial Intelligence:
Let us look a little more in detail about the various and most effective Python libraries for AI:
TensorFlow:
TensorFlow was developed by Google. This library is very useful in writing Machine Learning (ML) algorithms and also to perform huge computations that involve Neural Networks.
NumPy:
NumPy is a Python library mainly used for computing scientific and mathematical data.
Theano:
Theano is a functional library that effectively calculates and computes mathematical expressions involving multi-dimensional arrays.
Keras:
This library simplifies the implementation of neural networks. It consists of impressive functionalities for computing models, evaluating data-sets, and visualizing graphs.
EasyAI:
EasyAI is a simple Python engine for two-player games with AI (Negamax, transposition tables, game solving)
Benefits and features of Python:
Python being an object-oriented scripting language offers many benefits and features, which include:
Platform-independent
Python possess the ability to run on all operating systems and it is an open-source programming language. It offers flexible usage with fewer modifications required in basic coding.
Easy interpretation
Python does not need to be compiled into ML before execution but can be run directly by the programmer with the help of native ML, which is known to the hardware. It is useful for a faster and simplified interpretation by an emulator or virtual machines.
General purpose and high-level programming language
Python is very helpful as it can be used over several technologies and domains. Python is especially used for dealing with many variables, arrays, complex arithmetic, objects, Boolean expressions, and various other abstract concepts to make it exhaustive for improving usability.
Automatic Memory Management
Python has a dynamic type system; it has programming templates such as imperative, object-oriented, functional and procedural features. It is available for all the operating systems allowing titled CPython that is garnering huge popularity.
Prebuilt libraries
Numpy for scientific computation, PyBrain for Python ML, and Scipy for advances computing are the libraries to make Python the best suited programming language for AI.
Robust community
Globally, Python developers provide wide support and assistance through forums-and tutorials to help; this helps a developer to write code easier.
To know more about AI and Python you can read CBSE AI Best Book | CBSE Python Best Book