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ACCENTURE | COGNIZANT | IBM | CAPGEMINI

ACCENTURE | COGNIZANT | IBM | CAPGEMINI

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Got selected in Accenture 🥳🥳🥳 100% clear for any Company with interview interview Guidance ✅ Contact: @mlcoder2

Who wins the game ✅ Contact: @mlcoder2 #Google

def find(parent, u): if parent[u] != u: parent[u] = find(parent, parent[u]) return parent[u] def unite(parent, rank, u, v): root_u = find(parent, u) root_v = find(parent, v) if root_u != root_v: if rank[root_u] > rank[root_v]: parent[root_v] = root_u elif rank[root_u] < rank[root_v]: parent[root_u] = root_v else: parent[root_v] = root_u rank[root_u] += 1 def solve(n, edges): edges.sort(key=lambda x: x[2]) parent = list(range(n + 1)) rank = [0] * (n + 1) cost = 0 edges_used = 0 for u, v, c in edges: if find(parent, u) != find(parent, v): unite(parent, rank, u, v) cost += c edges_used += 1 if edges_used == n - 1: break return cost Break and Add ✅ #Google

def findMinChanges(taskDependency):     n = len(taskDependency)     changes = 0     final_task = -1         for i in range(n):         if taskDependency[i] == i + 1:             final_task = i + 1             break         if final_task == -1:         final_task = n         changes += 1         visited = set()     for i in range(1, n + 1):         if i not in visited:             current = i             path = set()             while current not in visited:                 if current == final_task:                     break                 if current in path:                     # Found a cycle, break it                     changes += 1                     break                 path.add(current)                 visited.add(current)                 current = taskDependency[current - 1]     for i in range(1, n + 1):         if i != final_task and taskDependency[i - 1] == i:             changes += 1         return changes Taks Dependency ✅ #Gameskraft

def solve(A, N, M, L, x): B = A[:] op = 0 for i in range(N): if B[i] > x: dec = B[i] - x length = min(L, N - i) for j in range(length): B[i + j] -= dec op += dec if op > M: return False return True def minimize_max_element(A, N, M, L): low = min(A) high = max(A) while low < high: mid = low + (high - low) // 2 if solve(A, N, M, L, mid): high = mid else: low = mid + 1 return low Array and queries ✅ #Google

def collect_max(mat): n = len(mat) if n == 0: return 0 dp = [[[ -1 for _ in range(2)] for _ in range(n)] for _ in range(n)] dp[0][0][1] = 1 if mat[0][0] == 1 else 0 for i in range(n): for j in range(n): if mat[i][j] == -1: continue if i > 0 and dp[i-1][j][1] != -1: dp[i][j][1] = max(dp[i][j][1], dp[i-1][j][1] + (1 if mat[i][j] == 1 else 0)) if j > 0 and dp[i][j-1][1] != -1: dp[i][j][1] = max(dp[i][j][1], dp[i][j-1][1] + (1 if mat[i][j] == 1 else 0)) if dp[n-1][n-1][1] == -1: return 0 dp[n-1][n-1][0] = dp[n-1][n-1][1] for i in range(n-1, -1, -1): for j in range(n-1, -1, -1): if mat[i][j] == -1: continue if i < n-1 and dp[i+1][j][0] != -1: dp[i][j][0] = max(dp[i][j][0], dp[i+1][j][0] + (1 if mat[i][j] == 1 else 0)) if j < n-1 and dp[i][j+1][0] != -1: dp[i][j][0] = max(dp[i][j][0], dp[i][j+1][0] + (1 if mat[i][j] == 1 else 0)) return dp[0][0][0] Airport Limousine ✅ #GamesKraft

import heapq def get_greatest_elements(arr, k): n = len(arr) result = [] min_heap = [] for i in range(n): heapq.heappush(min_heap, arr[i]) if len(min_heap) > k: heapq.heappop(min_heap) if i >= k - 1: result.append(min_heap[0]) return result Get Greatest Elements ✅ #GamesKraft

from collections import defaultdict def getMaxRacers(speed, k):     ans = 0     D = defaultdict(list)     for i, e in enumerate(speed):         D[e].append(i)     for arr in D.values():         l = 0         for r in range(len(arr)):             while r > l and arr[r] - arr[l] - (r - l) > k:                 l += 1             ans = max(ans, r - l + 1)         return ans Max Racers ✅ #GamesKraft

def answer(arr, i, dp): if i >= len(arr): return 0 if dp[i] != -1: return dp[i] include = arr[i] | answer(arr, i + 1, dp) exclude = answer(arr, i + 1, dp) dp[i] = max(include, exclude) return dp[i] def solve(N, arr): dp = [-1] * N return answer(arr, 0, dp) OR Bit ✅ #Seimens

def solve(N, workload): tot = 0 max_tot = 0 for i in workload: if i > 6: tot += 1 else: tot = 0 if tot > max_tot: max_tot = tot return max_tot peak output ✅ #Seimens

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Capgemini done successfully ✅✅✅✅ 100% clearance for any exam ✅ Contact: @mlcoder2
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Capgemini done successfully ✅✅✅✅ 100% clearance for any exam ✅ Contact: @mlcoder2

CAPGEMINI ✅
CAPGEMINI ✅

Capgemini Round-1 Cleared ✅
Capgemini Round-1 Cleared ✅

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