Why Python is Best Suited for Machine Learning?

Python is a widespread programming language nowadays. Since the advent of computers programming languages has a key role to play. They have been used in almost all fields nowadays. The data scientists use Python as a key language for the analysis of data and to find out insights. In the medical field also use python for patient booking, medicine prescription, test analysis, etc. Most of the applications on phone and the web are working based on python language. The key feature of python that makes it famous among users is dynamic typing and dynamic binding.

Machine learning can be explained as a part of Artificial Intelligence. It allows the software to become independent in taking decisions. Machine learning programs software to do this function. This software learns from trends or recent activities and makes decisions. Machine learning helps a business to find out the trends and patterns and the behavior of the customers. Machine Learning helps in the development of new products. In most companies Machine learning become a key component.

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Useful features of Python

Python is used in Machine learning as well as in Data Science. There are some features of python used by Data science and Machine learning for their work. Apart from this Python has a lot of useful features provided to the users. Let us look into it.

• Python uses elegant syntax, which makes the programs easier to read
• Simple to access the python language
• Easy to achieve program working
• Huge library support and Huge community support
• Simple to test codes using interactive mode
• Simple to extend the codes
• It is an expressive language
• Multiplatform codes. Users can use the same code on different platforms
• In a couple of categories, Python is a free software

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Python for Data Science

Data scientist collects data, analyzes it, and make interpretations to get insights. Python is one of the best languages used by data scientists. Data scientists use mathematical and statistical tools for various projects and applications. Python language provides functions based on mathematics and statistics which helps data scientists to complete their work easily. Python also offers a wide range of scientific research communities which helps data scientists to get support for their work. The most commonly used libraries of python in data science are:

1. Numpy
2. Pandas
3. Matplotlib
4. Scipy
5. Scikit-Learn

Python in Machine Learning

Machine learning is always focussing on the future. Artificial Intelligence and Machine learning, both are making software or machines to learn by themselves using the recent trends or experience to make decisions. They always look forward to the future. Prediction of the future can be done with the help of Machine learning. Why Python is suited for Machine learning is that it offers a lot of AI and ML projects in today’s world. Python is stable and flexible and a lot of tools are available for Machine learning projects. Let us look at the key features of pythons that are helpful in Machine learning projects.

• Simple and Consistent

Python codes are very easy and simple to write. It offers reliable codes to the users. Mostly complex algorithms and versatile workflows stand behind Artificial Intelligence and Machine Learning. The general-purpose nature of python language helps in doing complex tasks of machine learning and it enables the users to build the prototypes quickly.

• Selection of Libraries and Frameworks

Libraries and frameworks are used by the developers to reduce the run time. Python is rich in its libraries and frameworks. The common libraries of python used in Machine learning are Keras, Tensorflow and Sci-kit learn.

• Independent Platform

Python’s greatest advantage is that it is a platform-independent language. It supports many platforms. A code written in python language can be used on multiple platforms without any changes or with minimal changes. This helps the developers to work only on a single code.

• Community and Popularity

Python offers great community support to its developers. If the developers are having doubts, they can make use of the communities. And also the popularity of Python is another added advantage of python. When it comes to machine language community support helps in making complex algorithms easy and interpretable.

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Conclusion

Python is a famous programming language that offers great support to its developers. It is best suited to machine language because of its simplicity, frameworks, library support, and community support. The popularity of python can also help work with machine language. Python helps machine learning in making meaningful insights and decision making.