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2818. Apply Operations to Maximize Score | Monotonic Stack & Prime Factorization | Python Solution

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In this video, we solve Leetcode 2818: Apply Operations to Maximize Score using Python.
The problem requires us to maximize the final score by selecting numbers optimally while considering their prime factorization count. We will use monotonic stack, sorting, and modular exponentiation to efficiently compute the result.
What You'll Learn:
✅ Understanding prime factorization scoring and its significance.
✅ Efficient use of the monotonic stack for range queries.
✅ Sorting and greedy selection techniques for optimal scoring.
✅ Implementing modular exponentiation to handle large numbers.
✅ Optimized time complexity for better performance in coding interviews.
Why Watch This Video?
🚀 Enhance your competitive programming skills with advanced techniques.
⚡ Master monotonic stack to solve range-based problems efficiently.
⚡ Learn greedy algorithms combined with sorting tricks.
💡 Step-by-step explanation with intuitive dry-run for better understanding.
Keywords
Maximum Score from Applying Operations
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Python subarray problems
Modular exponentiation in Python
Sorting and greedy algorithms Python
Python optimization techniques
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Leetcode mathematical problems
Maximum product subarray problems Python
Python best coding practices
Array transformation problems in Python
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Sliding window and monotonic stack Python
Python advanced problem-solving techniques
Efficient multiplication strategies Python
Greedy and sorting-based problems Python
Number theory and factorization problems Python
Optimized mathematical algorithms Python
Python modulo operations optimization
Python large number computations
Python efficient exponentiation techniques
Python prime factor decomposition
Data structure and algorithms Python
Leetcode sorting and greedy problems
Monotonic stack and range queries Python
Subarray optimization problems in Python
Python time complexity optimization
Python advanced DSA concepts
Python implementation of number theory algorithms
Python dynamic programming and greedy mix
Competitive programming techniques in Python
Optimizing large calculations in Python
Python programming for coding interviews
Python advanced sorting and searching problems
Factorization-based problem-solving in Python
Modular arithmetic tricks in Python
Efficient coding practices for Python
Python number manipulation tricks
Prime decomposition and usage in coding
Python data structure implementation for optimization
Coding interview tricks and techniques Python
Leetcode problem-solving in Python
The problem requires us to maximize the final score by selecting numbers optimally while considering their prime factorization count. We will use monotonic stack, sorting, and modular exponentiation to efficiently compute the result.
What You'll Learn:
✅ Understanding prime factorization scoring and its significance.
✅ Efficient use of the monotonic stack for range queries.
✅ Sorting and greedy selection techniques for optimal scoring.
✅ Implementing modular exponentiation to handle large numbers.
✅ Optimized time complexity for better performance in coding interviews.
Why Watch This Video?
🚀 Enhance your competitive programming skills with advanced techniques.
⚡ Master monotonic stack to solve range-based problems efficiently.
⚡ Learn greedy algorithms combined with sorting tricks.
💡 Step-by-step explanation with intuitive dry-run for better understanding.
Keywords
Maximum Score from Applying Operations
Leetcode 2818 solution in Python
Prime factorization problems in Python
Python modular arithmetic coding
Python competitive programming
Monotonic stack problems in Python
Python Leetcode solutions
Prime factorization optimization Python
Greedy algorithm problems in Python
Python coding interview questions
Python FAANG interview questions
Efficient prime factor counting Python
Python subarray problems
Modular exponentiation in Python
Sorting and greedy algorithms Python
Python optimization techniques
Python number theory problems
Coding interview preparation Python
Python DSA for competitive programming
Leetcode mathematical problems
Maximum product subarray problems Python
Python best coding practices
Array transformation problems in Python
Leetcode medium difficulty problems
Sliding window and monotonic stack Python
Python advanced problem-solving techniques
Efficient multiplication strategies Python
Greedy and sorting-based problems Python
Number theory and factorization problems Python
Optimized mathematical algorithms Python
Python modulo operations optimization
Python large number computations
Python efficient exponentiation techniques
Python prime factor decomposition
Data structure and algorithms Python
Leetcode sorting and greedy problems
Monotonic stack and range queries Python
Subarray optimization problems in Python
Python time complexity optimization
Python advanced DSA concepts
Python implementation of number theory algorithms
Python dynamic programming and greedy mix
Competitive programming techniques in Python
Optimizing large calculations in Python
Python programming for coding interviews
Python advanced sorting and searching problems
Factorization-based problem-solving in Python
Modular arithmetic tricks in Python
Efficient coding practices for Python
Python number manipulation tricks
Prime decomposition and usage in coding
Python data structure implementation for optimization
Coding interview tricks and techniques Python
Leetcode problem-solving in Python