This article provides an overview of Python and its application to Data Science and Machine Learning and why it is important.
Originally published by Chris Kambala at dzone.com
Python is a general-purpose, high-level, object-oriented, and easy to learn programming language. It was created by Guido van Rossum who is known as the godfather of Python.
Python is a popular programming language because of its simplicity, ease of use, open source licensing, and accessibility — the foundation of its renowned community, which provides great support and help in creating tons of packages, tutorials, and sample programs.
Python can be used to develop a wide variety of applications — ranging from Web, Desktop GUI based programs/applications to science and mathematics programs, and Machine learning and other big data computing systems.
Let’s explore the use of Python in Machine Learning, Data Science, and Data Engineering.Machine Learning
Machine learning is a relatively new and evolving system development paradigm that has quickly become a mandatory requirement for companies and programmers to understand and use. See our previous article on Machine Learning for the background. Due to the complex, scientific computing nature of machine learning applications, Python is considered the most suitable programming language. This is because of its extensive and mature collection of mathematics and statistics libraries, extensibility, ease of use and wide adoption within the scientific community. As a result, Python has become the recommended programming language for machine learning systems development.Data Science
Data science combines cutting edge computer and storage technologies with data representation and transformation algorithms and scientific methodology to develop solutions for a variety of complex data analysis problems encompassing raw and structured data in any format. A Data Scientist possesses knowledge of solutions to various classes of data-oriented problems and expertise in applying the necessary algorithms, statistics, and mathematic models, to create the required solutions. Python is recognized among the most effective and popular tools for solving data science related problems.Data Engineering
Data Engineers build the foundations for Data Science and Machine Learning systems and solutions. Data Engineers are technology experts who start with the requirements identified by the data scientist. These requirements drive the development of data platforms that leverage complex data extraction, loading, and transformation to deliver structured datasets that allow the Data Scientist to focus on solving the business problem. Again, Python is an essential tool in the Data Engineer’s toolbox — one that is used every day to architect and operate the big data infrastructure that is leveraged by the data scientist.Use Cases for Python, Data Science, and Machine Learning
Here are some example Data Science and Machine Learning applications that leverage Python.
This article provided an overview of Python and its application to Data Science and Machine Learning and why it is important.
Originally published by Chris Kambala at dzone.com
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This Edureka video on 'Python For Data Science - How to use Data Science with Python - Data Science using Python ' will help you understand how we can use python for data science along with various use cases. What is Data Science? Why Python? Python Libraries For Data Science. Roadmap To Data Science With Python. Data Science Jobs and Salary Trends
This Edureka video on 'Python For Data Science - How to use Data Science with Python - Data Science using Python
' will help you understand how we can use python for data science along with various use cases. Following are the topics discussed this Python Data Science Tutorial:
This video will focus on the top Python libraries that you should know to master Data Science and Machine Learning. Here’s a list of topics that are covered in this session:
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