12.25

Positive

Binary encoding

F1 score

High - dimensional data

High training error and high test error

#include <bits/stdc++.h>
using namespace std;

class Solution {
public:
string clearStars(string A) {
string s = A;

priority_queue<char, vector<char>, greater<char>> pq;
vector<vector<int>> ind(26);
unordered_set<int> rs;

for (int i = 0; i < s.size(); ++i) {
if (s[i] == '*') {
rs.insert(i);
char ch = pq.top(); pq.pop();
pq.push(ch);

rs.insert(ind[ch - 'a'].back());
ind[ch - 'a'].pop_back();

if (ind[ch - 'a'].empty()) pq.pop();

continue;
}

if (ind[s[i] - 'a'].empty())
pq.push(s[i]);

ind[s[i] - 'a'].push_back(i);
}

string res = "";
for (int i = 0; i < s.size(); ++i) {
if (!rs.count(i)) {
res += s[i];
}
}

return res;
}
};


Clear stars
Start removal
C++

Python
Start removal

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Role: Software Engineer(Backend)
Experience: 0- 1Years
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1/2

4xy

4

30/84

150

Prior x Likelihood

C

Mode>median>mean

S2: 4xy
S7: 6
S12: 0
Q4: 1/2
S22: (2, 3)
S28: Target/Mean Encoding
S29: TimeSeriesSplit
S38: 15
S43: 2/5
S59: Mode > Median > Mean

ML - 2: The data has a Gaussian distribution
ML - 7: Updating prior beliefs with observed data using Bayes' theorem
ML - 12: The probability distribution over actions given states
ML - 17: Internal covariate shift
ML - 23: Boosting reduces bias, bagging reduces variance
ML - 24: Binary Cross-Entropy
S48: 30/84
S60: 150
S53: 2/3
S68: Prior × Likelihood


Amazon Machine Learning Summer School:

Exam Date: 3rd August 2025
Exam Duration: 60 mins

10:30 AM

Test format:
Section 1 - MCQ section - 20 questions
Section 2 - DSA type coding section - 2 questions

Answers available 👇👇👇
Telegram channel:- @allcoding1_official