15 July 2019
Machine learning has become a hot topic over the last few years, not just with programmers, data scientists, and other IT professionals, but also with the wider public. When it comes to machine learning, Python is the preferred programming language due to its consistent syntax, short development time, and overall simplicity.
Python is now the fastest growing major programming language, and second only to Rust as the most loved programming language. It’s clear that Python is transforming the fields of machine learning, data science, and the wider AI movement, but why is Python best suited for machine learning, and how is it helping businesses unlock their data?
What Makes Python Great for Data Analysis
While Python is considered a general-purpose programming language, it has become the preferred language for scientific and mathematical systems. You will find that projects relating to Finance, Big Data, automation, scripting, computer graphics, and other mathematical computing will rely heavily on Python. Python is used extensively in the FinTech industry for stock market analysis, stock predictions, machine learning, and even in the code for ATM machines. Python is well suited to the Financial industry because it’s syntax is close to mathematical syntax which allows for increased flexibility. This also applies to data Science where data scientists are utilizing python to analyze data to gain actionable insights.
Python is also favored in data science because it’s relatively easy to learn and has a gradual learning curve compared to some other popular programming languages, such as Java. This increases the accessibility of Python which encourages more programmers to learn it. Python is also Open Source which again increases its accessibility to users.
As a popular programming language, Python also has a large online community of programmers who share their knowledge to advance Python programmers and the projects they are working on. The online community of Python developers is also busy developing open source Python packages for a multitude of applications. For example, if you want your Python application to work with images you can use Numpty or Opencv, if you want it to analyze audio you can use Librosa, and if you want to solve machine learning problems you can use panda or Scikit.
How Python Based AI and Machine Learning Is Helping Transform Business
The amount of data we are producing every day is growing at a rapid rate. The digital universe is doubling in size every two years and will be 44 zettabytes in size by 2020. To put this into perspective further in 2013 the digital universe was 4.4 zettabytes in size. Using python for data analysis and machine learning can help unlock the potential in this data and turn vast libraries of information into actionable goals for businesses.
And this is increasingly what businesses are doing all over the world. Businesses are using big data to transform their marketing practices, their forecasting, bookkeeping, and more.
In order to unlock this data, businesses need to have efficient data collection and data analysis policies to ensure their data can be utilized in a meaningful way and lead to improved business outcomes. This is why businesses are investing more heavily in AI and machine learning friendly languages such as Python in order to adapt to the market and stay ahead.
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