Python has recently gained fame over the programming world and currently it is one of the most popular languages in the world. Developers are choosing python for projects ranging from web development to scripting and process automation. Developers are using python for AI machine learning and deep learning projects. AI has created a great opportunity for developers to spotify artists and songs to users or netflix shows what you will see next. It is the same thing used by companies in customer service to drive self service, employee productivity and for improving workflows.
Is python good for AI? We can have a quick look at the main reasons why developers are choosing python programming language for machine learning and deep learning projects?
Before we start you should understand that deep learning is a subset of machine learning and machine learning is a subset of AI. In other words all machine learning is AI but all AI is not machine learning and so forth.
AI is essentially exhibited by any machine that leads to optimal solution to a given problem. Then machine learning takes the next step by using algorithm and passes the data and learns from that data to create informed decisions.
Deep learning is also working in a similar way but it has some capabilities. It takes decisions just like humans. It is done by the inspiration of a neural network of human brain by using layered structure algorithm. The result we get is a model that can learn multiple levels of representations according to different level of abstractions.
One of the main reasons why developers use python is because it has abundant libraries and frameworks that will help them to save coding and development time. Machine learning and deep learning are well designed for NumPy. It is used for scientific computation. SciPy is used for advanced computation. Scikit learn is used in data analysis and data mining.
These are the main popular libraries working along with heavy frameworks like apache spark and CNTK etc. In terms of machine learning and deep learning, libraries and frameworks work in python.
Python is basically ease of using, readable code and is almost unrivaled and simplicity especially for new developers. There are many advantages of ML and DL. Both ML and DL have complex algorithms at different stages of workflows. A new developer needs to worry about the coding because they focus more on solution to their problems. This helps them to easily achieve the goals of the project. The syntax of python is faster than any other programming language and allows the developer to test the code without having to implement them.
Actually python is an open source programming language and is supported by whole resources and high quality documentation. It also supports a large amount of developers willing to provide assistance and advice through all stages of development.
AI has a very important role in our world with new applications developing all the time. Smart developers use python because it has some benefits that makes it particularly suitable for ML & DL. Pythons selection of specific ML libraries and frameworks helps to reduce development time and process. It’s syntax and readability gives quick testing of complex algorithms and makes the language understandable to non programmers. It also reduces the pressure of developers and it helps them to concentrate on solving problems and achieving project goals. Syntax helps the developers to transfer and collaborate between projects. Python is also happy to support those who are willing to provide guidance or assistance to new developers which can be invaluable when dealing with such complex projects.
There are many other programming languages used for AI, there is no doubt in the fact that python is the cutting edge and should be given special significant consideration. That is why you should consider python as your AI project.