Understanding the Time Complexity of an Algorithm

Algorithms: Understanding the Time Complexity of an Algorithm
Topics discussed:
1. A Recap of Priori vs. Posteriori Analysis.
2. CPU Computations and Main Memory Space.
3. The Time Complexity of an Algorithm.

Music:
Axol x Alex Skrindo - You [NCS Release]

#AlgorithmsByNeso #Algorithms #TimeComplexity

[diwanshsawlani]

00:08 Understanding priori vs posterior analysis of time and space complexity
03:16 Understanding Priori Analysis for Algorithm Time Complexity
06:26 Time complexity is the estimation of total CPU computations required to execute an algorithm.
09:34 Analyzing the time complexity of a simple algorithm with frequency count method
12:32 Understanding time complexity of algorithm instructions
15:38 The frequency count of the instruction is n + 1.
18:24 The time complexity of the algorithm depends on the number of times certain instructions are executed.
21:10 Understanding time complexity of an algorithm
23:47 Time complexity of algorithm is Big O

[TanvirAhmedOriginal]

Thank you Neso Academy, for making our life easier.

[Think_First]

Thank you for sharing in depth knowledge 🙏

[subhamukherjee]

Thanks you..this video has helped me...need more videos on DSA topic

[akashtiwari]

Plz bring series of gate pyq year wise subject wise

[eghanshith]

1.Priori vs. Posterior Analysis Recap:
Priori analysis estimates time and memory space before executing an algorithm.
Posterior analysis calculates them after execution.

2.CPU Computations and Main Memory Space:
CPU computations refer to tasks executed by the CPU (instructions).
Main memory space stores data and instructions for quick access during execution.

3.Time Complexity Estimation:
Use the frequency count method.
Calculate the sum of frequency counts for each instruction.
Example: sum = 0 (1 unit), for (i = 1; i <= n; i++) (n + 1 units), sum += a[i] (2n units), return sum (1 unit).

4.Overall Time Complexity:
Total frequency count: 4n + 4.
Dominant term: 4n.
Time complexity: Big O(n) (linear time).

[yazidbessadet]

so much AURA i'm feeling right now cant lie LOL. NESO are the best

[alfianabdulhalin]

Although in the end, the main answer we're looking for is O(n)... just wondering about the sum = sum + a[i] part. Isn't it supposed to be 1? Because it's a one liner... I'm thinking in terms if we assign values to variables, say .... int a = 0, j = 9; <-- This would still be 1 unit of time, right? Thanks :)

[Ehvan]

one thing i could say is just thanks
i think that is very small one

[Gust]

Sir can you pls bring a course on networking? Like the many topics covered in ccna networking exam pls. It will add a depth of knowledge tobus and prepare us for that exam 🙏

[Debe-]

For increment what I'd the time complexity

[TanvirAhmedOriginal]

I don't understand why not O(4n+4)