AI & MACHINE LEARNING PROGRAM • LEVEL 20 — NATURAL LANGUAGE PROCESSING

Compare Text Vectors with Python

Learn compare text vectors with python with a short, executable Python example.

IntermediateCosine similarityText vector

PROBLEM UNDERSTANDING

Input and expected output

Sample input

No input required

Sample output

0.5

COMPLETE PYTHON PROGRAM

Complete Python implementation

from math import sqrt
a,b=[1,1,0],[1,0,1]
score=sum(x*y for x,y in zip(a,b))/(sqrt(sum(x*x for x in a))*sqrt(sum(y*y for y in b)))
print(round(score,3))

CURRENT STEP

Select Start to walk through the important lines.

SELECTED LINE

No line selected

EXPECTED OUTPUT FOR THE SAMPLE

0.5

0%Step 0 of 0

PROGRAM EXPLANATION

Algorithm and explanation

Import the required standard-library tools and prepare the sample data for compare text vectors.
Process the data step by step using Cosine similarity and Text vector.
Display the result for compare text vectors and compare it with the documented sample output.

This example of compare text vectors processes the sample values in a controlled iteration. It demonstrates Cosine similarity and Text vector and prints a deterministic result that can be checked against the sample output.

EFFICIENCY

Time and space complexity

Time complexity

O(n)

Auxiliary space

O(1)

DEBUGGING CHECKLIST

Common mistakes

Check this

For compare text vectors, keep the data shape and value types consistent with Cosine similarity.

Check this

Keep every dependent statement inside the correct indented Python block.

Check this

Check denominators, numeric ranges and rounding before comparing the calculated value.

Try it yourself

Practice: Run the program with the sample input, predict its output, and then test one boundary case of your own.