In this tutorial, you will learn about linear search. Also, you will find working examples of linear search in Python.
Linear search is the simplest searching algorithm that searches for an element in a list in sequential order. We start at one end and check every element until the desired element is not found.
How Linear Search Works?
The following steps are followed to search for an element
k = 1 in the list below.
- Start from the first element, compare k with each element x.
x == k, return the index.
- Else, return not found.
Linear Search Algorithm
LinearSearch(array, key) for each item in the array if item == value return its index
/* Linear Search in Python */ def linearSearch(array, n, x): /* Going through array sequentially */ for i in range(0, n): if (array[i] == x): return i return -1 array = [2, 4, 0, 1, 9] x = 1 n = len(array) result = linearSearch(array, n, x) if(result == -1): print("Element not found") else: print("Element found at index: ", result)
Linear Search Complexities
Time Complexity: O(n)
Linear Search Applications
- For searching operations in smaller arrays (<100 items).
Python Example for Beginners
Two Machine Learning Fields
There are two sides to machine learning:
- Practical Machine Learning:This is about querying databases, cleaning data, writing scripts to transform data and gluing algorithm and libraries together and writing custom code to squeeze reliable answers from data to satisfy difficult and ill defined questions. It’s the mess of reality.
- Theoretical Machine Learning: This is about math and abstraction and idealized scenarios and limits and beauty and informing what is possible. It is a whole lot neater and cleaner and removed from the mess of reality.
Data Science Resources: Data Science Recipes and Applied Machine Learning Recipes
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