{"id":16544,"date":"2020-07-30T20:14:10","date_gmt":"2020-07-30T14:44:10","guid":{"rendered":"https:\/\/www.mygreatlearning.com\/blog\/data-preprocessing\/"},"modified":"2024-09-03T18:00:17","modified_gmt":"2024-09-03T12:30:17","slug":"data-preprocessing","status":"publish","type":"post","link":"https:\/\/www.mygreatlearning.com\/blog\/data-preprocessing\/","title":{"rendered":"Data Preprocessing Introduction, Concepts and Definition?"},"content":{"rendered":"\n

What is data preprocessing?<\/strong><\/h2>\n\n\n\n

For machine learning, we need data. Lots of it. The more we have, the better our model. Machine learning algorithms are data-hungry. But there\u2019s a catch. They need data in a specific format.<\/p>\n\n\n\n

In the real world, several terabytes of data is generated by multiple sources. But all of it is not directly usable. Audio, video, images, text, charts, logs all of them contain data. But this data needs to be cleaned in a usable format for the machine learning algorithms to produce meaningful results.<\/p>\n\n\n\n

The process of cleaning raw data for it to be used for machine learning activities is known as data preprocessing. It\u2019s the first and foremost step while doing a machine learning project. It\u2019s the phase that is generally most time-taking as well.<\/p>\n\n\n\n

Why data \u2013 preprocessing?<\/strong><\/h2>\n\n\n\n

Real-world data is often noisy, incomplete with missing entries, and more often than not unsuitable for direct use for building models or solving complex data-related problems. There might be erroneous data, or the data might be unordered, unstructured, and unformatted. <\/p>\n\n\n\n

The above reasons render the collected data unusable for machine learning purposes. It\u2019s seen that the same data when formatted and cleaned produces more accurate and reliable results when used by machine learning models other than their unprocessed counterparts.<\/p>\n\n\n\n

Data pre-processing steps<\/p>\n\n\n\n

In data pre-processing several stages or steps are there. All the steps are listed below -<\/p>\n\n\n\n