Python for Business: Optimize Pre-Processing Data for Decision-Making

摘要： There are a number of powerful advantages of using Python for data preprocessing.

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The rise of machine learning and the use of Artificial Intelligence gradually increases the requirement of data processing. That’s because the machine learning projects go through and process a lot of data, and that data should come in the specified format to make it easier for the AI to catch and process.

Likewise, Python is a popular name in the data preprocessing world because of its ability to process the functionalities in different ways. Besides, libraries like Pandas and Numpy make Python one of the most efficient technologies available in the market.

In this article, we will discuss how Python runs data preprocessing with its exhaustive machine learning libraries and influences business decision-making.

Data Preprocessing is a Requirement

Data preprocessing is converting raw data to clean data to make it accessible for future use. Elaborately, the steps and methods to organize and reshape the data to execute it suitably for use or mining, the entire process, in short, known as Data Preprocessing.

With technological advancement, information has become one of the most valuable elements in this modern era of science. However, data comes in different sizes and formats (text, images, audio, video, etc.). Hence, it’s mandatory to preprocess the data to provide it in the final use.

Accordingly, before using that data in machine learning or an algorithm, you need to convert it into a precise format suitable for the system to inherit it. For instance, the Random Forest Algorithm in Python doesn’t support null values. Hence, it would help if you preprocessed the null values before using the data in the Random Forest algorithm.

Therefore, if you don’t preprocess the data before applying it in the machine learning or AI algorithms, you are most likely to get wrong, delayed, or no results at all. Hence, data preprocessing is essential and required.

Python as a Data Processing Technology

Comprehensive data processing requires robust data analysis, statistics, and machine learning. As a high-level, open-source programming language, Python possesses a firm grip over these functionalities. Consequently, Python has become one of the most efficient instruments for data preprocessing.

轉貼自： Smart Data Collective

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