Dharaneish V C

  DATA PREPROCESSING The objective of data pre-processing is to analyze, filter, transform, and encode data so that a machine learning algorithm can understand and work with the processed output. The phrase "garbage in, garbage out" is very much apt to data mining and machine learning projects. The presence of any unclean data like missing attributes, attribute values, containing noise or outliers, and duplicate or wrong data will degrade the quality of the ML results. So, It is important to manipulate or transform the raw data in a useful and efficient format before it is used in Machine learning to ensure or enhance performance. Important Libraries for Data Preprocessing: To do data preprocessing in Python, we need to import some predefined Python libraries. These libraries are used to perform some specific tasks. There are three specific libraries that we will use for data preprocessing. ·        Numpy : The Numpy Python library is used to include many kinds of mat