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Best Practices for Handling Duplicate Elements in Python Lists

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Here are three awesome ways that you can use to remove duplicates in a list. These are helpful in resolving your data analytics solutions.  01. Using a Set Convert the list into a set , which automatically removes duplicates due to its unique element nature, and then convert the set back to a list. Solution: original_list = [2, 4, 6, 2, 8, 6, 10] unique_list = list(set(original_list)) 02. Using a Loop Iterate through the original list and append elements to a new list only if they haven't been added before. Solution: original_list = [2, 4, 6, 2, 8, 6, 10] unique_list = [] for item in original_list:     if item not in unique_list:         unique_list.append(item) 03. Using List Comprehension Create a new list using a list comprehension that includes only the elements not already present in the new list. Solution: original_list = [2, 4, 6, 2, 8, 6, 10] unique_list = [] [unique_list.append(item) for item in original_list if item not in unique_list] All three methods will result in uni

Quick Guide: Machine Learning Examples and Uses

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I want to share with you the best real-time examples on machine learning.  Because of new computing technologies, machine learning today is not like machine learning of the past.  While many machine learning algorithms have been around for a long time, the ability to automatically apply complex mathematical calculations to big data – over and over, faster and faster – is a recent development. Machine learning use cases The heavily hyped, self-driving Google car? The essence of machine learning.  Online recommendation offers like those from Amazon and Netflix? Machine learning applications for everyday life.  Knowing what customers are saying about you on Twitter? Machine learning combined with linguistic rule creation.  Fraud detection? One of the more obvious, important uses in our world today. Best example : "pattern recognition" is best example for Machine Learning Related: Take Quiz on Machine Learning Where can you apply machine learning.