Artificial Intelligence with Python

Artificial Intelligence has been around for over half a century now and its advancements are growing at an exponential rate. This blog on Artificial Intelligence With Python will help you understand all the concepts of AI with practical implementations in Python. 

Why Is Python Best For AI?

Despite being a general-purpose language, Python has made its way into the most complex technologies such as Artificial Intelligence, Machine Learning, Deep Learning, and so on.

Why has Python gained so much popularity in all these fields?

Here is a list of reasons why Python is the choice of language for every core Developer, Data Scientist, Machine Learning Engineer, etc: 

• Less Code: Implementing AI involves tons and tons of algorithms. Thanks to Python's support for pre-defined packages, we don’t have to code algorithms. And to make things easier, Python provides a “check as you code” methodology that reduces the burden of testing the code.

• Prebuilt Libraries: Python has 100s of pre-built libraries to implement various Machine Learning and Deep Learning algorithms. So every time you want to run an algorithm on a data set, all you have to do is install and load the necessary packages with a single command. Examples of pre-built libraries include NumPy, Keras, Tensorflow, Pytorch, and so on.

• Ease of learning: Python uses a very simple syntax that can be used to implement simple computations like, the addition of two strings to complex processes such as building a Machine Learning model.

• Platform Independent: Python can run on multiple platforms including Windows, macOS, Linux, Unix, and so on.

• Massive Community Support: Python has a huge community of users which is always helpful when we encounter coding errors.

So to conclude, due to its ease of learning and usage, python codes can be easily written and executed much faster than other programming languages.