Today I focused on understanding time complexity and Big-O notation. I learned how to evaluate the efficiency of algorithms by analyzing the number of operations performed as the input size grows. Understanding complexity helps in writing optimized and scalable solutions.
Key takeaways
01
Understand constant, linear and quadratic complexity
02
Difference between worst and average case
03
Importance of optimization
04
Reading nested loops
05
Choosing better algorithms
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