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1. Consider the following algorithm: for ( i = 1 ; i <= 1 . 5 n ; i++) cout << i ; for ( i = n ; i >= 1 ; i - - ) cout << i ; (a) What is the output when n = 2, n = 4, and n = 6? (b) What is the time complexity T(n)? You may assume that the input n is divisible by 2.
1 2653Consider the following algorithm: j = 1 ; while ( j <= n/2) { i = 1 ; while ( i <= j ) { cout << j << i ; i++; } j++; } (a) What is the output when n = 6, n = 8, and n = 10? (b) What is the time complexity T(n)? You may assume that the input n is divisible by 2.
1 5467Consider the following algorithm: for ( i = 2 ; i <= n ; i++) { for ( j = 0 ; j <= n) { cout << i << j ; j = j + floor(n/4) ; } } (a) What is the output when n = 4 (b) What is the time complexity T(n). You may assume that n is divisible 4.
1 1794Consider the following algorithm, where the array A is indexed 1 through n: int add_them ( int n , int A[ ] ) { index i , j , k ; j = 0 ; for ( i = 1 ; i <= n ; i++) j = j + A[i] ; k = 1 ; for ( i = 1 ; i <= n ; i++) k = k + k ; return j + k ; } (a) If n = 5 and the array A contains 2, 5, 3, 7, and 8, what is returned? (b) What is the time complexity T(n) of the algorithm?
1 2519Give an algorithm for the following problem. Given a list of n distinct positive integers, partition the list into two sublists, each of size n/2, such that the difference between the sums of the integers in the two sublists is minimized. You may assume that n is a multiple of 2.
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Explain the difference between supervised, unsupervised, and reinforcement learning.
What is model interpretability, and why is it important?
What measures can ensure the robustness of AI systems?
What challenges do organizations face in implementing fairness in AI models?
Why is data considered crucial in AI projects?
How do Generative AI models create synthetic data?
Tell us do you have research experience in machine learning?
Explain the concept of SHAP and its role in XAI.
What techniques can improve the explainability of AI models?
How can AI be used to predict patient outcomes?
How do you identify and mitigate bias in Generative AI models?
What is your understanding of the different types of cloud-based machine learning services?
What challenges arise when implementing AI in finance?
What are some open problems you find interesting?
What ethical concerns arise when AI models are treated as "black boxes"?
