“Artificial intelligence, deep learning, machine learning – whatever you’re doing if you don’t understand it – learn it. Because otherwise you’re going to be a dinosaur within 3 years.” – Mark Cuban
Python is very much preferred by many developers throughout the machine learning community. There are a handful of reasons Python is a great fit for machine learning projects. It is a growing community.
Python’s Libraries
Python has an abundance of libraries including Numpy, Tensorflow, and Scikit-Learn. A library is a collection of functions and methods that allows the developer to perform many tasks without the need to write the code, saving the developers a lot of time.
Easy Code
Python is known for the simplicity style of code. For new developers, learning to code can be less frustrating than other coding languages like JavaScript or PHP. Machine learning is already complex to begin with, so developers favor a coding language less difficult. As well, simple code means faster development in testing algorithms.
The Support
Python is an open-source programming language and is widely supported throughout YouTube and GitHub. There are thousands of online courses to learn Python, but there is a monthly cost. The python community is very friendly and helpful to all types of developers. The community is always active providing assistance and advice to anyone in need.
Conclusion
Developers who are intelligent choose Python to be implemented into team’s machine learning projects. From the massive amount of libraries to friendly support from the Python community, this programming language should be the top-choice for all developers within the machine learning field. Recently, Python’s popularity continues to keep growing very quickly among data scientists, professors, and large corporations. In my opinion, Python is the programming language of choice for people who have a desire to try and apply machine learning to projects using data.
Anthony's Blog 