Maximizing House Robber Profit with Dynamic Programming

✅ Day 42 of 100 Days LeetCode Challenge Problem: 🔹 #204 – Count Primes 🔗 https://lnkd.in/gjsy54cm Learning Journey: 🔹 Today’s problem focused on counting the number of prime numbers less than a given integer. 🔹 I used the Sieve of Eratosthenes, an efficient algorithm for generating primes by iteratively marking multiples as non-prime. 🔹 Starting from 2, each prime eliminates its multiples, reducing unnecessary checks. 🔹 The remaining true values represent prime numbers. Concepts Used: 🔹 Sieve of Eratosthenes 🔹 Number Theory 🔹 Array Marking Technique 🔹 Optimization Key Insight: 🔹 Instead of checking each number individually, eliminating multiples significantly improves efficiency. 🔹 Starting from i² avoids redundant work because smaller multiples were already handled. 🔹 Preprocessing techniques like sieves are powerful for number-based problems. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

✅ Day 46 of 100 Days LeetCode Challenge Problem: 🔹 #91 – Decode Ways 🔗 https://lnkd.in/gpZQshBr Learning Journey: 🔹 Today’s problem focused on counting the number of ways to decode a numeric string into letters. 🔹 I used a Dynamic Programming approach with space optimization, tracking only the previous two states. 🔹 At each step, I checked both single-digit and two-digit decoding possibilities. 🔹 Careful handling of edge cases like leading zeros was essential to ensure valid decoding paths. Concepts Used: 🔹 Dynamic Programming 🔹 Space Optimization 🔹 String Parsing 🔹 State Transition Key Insight: 🔹 Many decoding problems depend on evaluating valid transitions from previous states. 🔹 Maintaining only necessary previous results reduces space complexity to O(1). 🔹 Edge cases involving zeros are critical in avoiding invalid combinations. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

✅ Day 26 of 100 Days LeetCode Challenge Problem: 🔹 #746 – Min Cost Climbing Stairs 🔗 https://lnkd.in/gzuqP_J3 Learning Journey: 🔹 Today’s problem focused on finding the minimum cost required to reach the top of a staircase. 🔹 I used Dynamic Programming to compute the minimum cost starting from each step and working backward. 🔹 At every step, the decision is to move one or two steps ahead, choosing the path with lower accumulated cost. 🔹 Storing intermediate results avoids redundant calculations and improves efficiency. Concepts Used: 🔹 Dynamic Programming 🔹 Bottom-Up DP 🔹 State Transition 🔹 Optimization Techniques Key Insight: 🔹 Problems involving minimum cost often benefit from a bottom-up approach. 🔹 Comparing future states helps determine the optimal current decision. 🔹 Dynamic Programming simplifies problems that would otherwise be exponential using recursion. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

✅ Day 36 of 100 Days LeetCode Challenge Problem: 🔹 #213 – House Robber II 🔗 https://lnkd.in/gmvFEbZe Learning Journey: 🔹 Today’s problem extended the classic House Robber problem by arranging houses in a circular layout. 🔹 The circular constraint means the first and last houses cannot both be robbed. 🔹 I solved this by breaking the problem into two linear cases: excluding the first house and excluding the last house. 🔹 A helper function applies the standard dynamic programming approach to maximize profit without adjacent selections. Concepts Used: 🔹 Dynamic Programming 🔹 Space Optimization 🔹 Problem Decomposition 🔹 Greedy Decision Making Key Insight: 🔹 Circular constraints can often be simplified by converting them into multiple linear scenarios. 🔹 Tracking only previous states reduces space complexity while maintaining optimal results. 🔹 Recognizing problem patterns helps reuse solutions from related problems. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

✅ Day 44 of 100 Days LeetCode Challenge Problem: 🔹 #3713 – Longest Balanced Substring 🔗 https://lnkd.in/gfryNgam Learning Journey: 🔹 Today’s problem focused on finding the longest substring where all characters appear with equal frequency. 🔹 I explored all possible substrings by fixing a starting index and expanding the window step by step. 🔹 A frequency array helped track character counts along with the number of distinct characters and maximum frequency. 🔹 By validating whether all active characters share the same count, I identified balanced substrings efficiently. Concepts Used: 🔹 String Processing 🔹 Frequency Counting 🔹 Nested Traversal 🔹 Sliding Window Concepts Key Insight: 🔹 Balanced substring problems rely on maintaining strict frequency conditions. 🔹 Tracking distinct characters and maximum frequency simplifies validation logic. 🔹 Smart bookkeeping can make brute-force approaches effective for constrained problems. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

✅ Day 40 of 100 Days LeetCode Challenge Problem: 🔹 #1200 – Minimum Absolute Difference 🔗 https://lnkd.in/gdXZxeGh Learning Journey: 🔹 Today’s problem focused on finding all pairs of elements with the minimum absolute difference in an array. 🔹 I first sorted the array so that the smallest differences would appear between adjacent elements. 🔹 By scanning the sorted list once, I tracked the minimum difference and collected all valid pairs. 🔹 This approach avoids unnecessary comparisons and improves efficiency. Concepts Used: 🔹 Sorting 🔹 Greedy Scanning 🔹 Array Traversal 🔹 Optimization Key Insight: 🔹 Sorting simplifies many comparison-based problems. 🔹 Minimum differences in a sorted array will always occur between neighboring elements. 🔹 Maintaining a running minimum helps build the result efficiently in one pass. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

Precision and logic are at the heart of every great application. 🔢 I recently developed a Simple Calculator project, focusing on creating a clean interface and robust arithmetic logic. This project was a fantastic way to practice Python functions and error handling to ensure every calculation is accurate and user-friendly. Check out the demo video below to see it in action! 🔗 GitHub Repository: https://lnkd.in/g8rrigDe #SoftwareEngineering #Coding #ProgrammingLogic #CalculatorProject #WebDevelopment #TechSkills

✅ Day 37 of 100 Days LeetCode Challenge Problem: 🔹 #322 – Coin Change 🔗 https://lnkd.in/gtfVrvhV Learning Journey: 🔹 Today’s problem focused on finding the minimum number of coins needed to make up a given amount. 🔹 I used Dynamic Programming with a bottom-up approach, building solutions for smaller amounts first. 🔹 A DP array tracks the minimum coins required for each value from 0 up to the target amount. 🔹 For every amount, I iterated through all coin denominations to compute the optimal solution. Concepts Used: 🔹 Dynamic Programming 🔹 Bottom-Up DP 🔹 Optimization Problems 🔹 State Transition Key Insight: 🔹 Breaking problems into smaller subproblems makes optimization manageable. 🔹 Initializing with infinity helps represent unreachable states clearly. 🔹 Iterative DP ensures efficient computation and avoids repeated work. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

✅ Day 39 of 100 Days LeetCode Challenge Problem: 🔹 #114 – Flatten Binary Tree to Linked List 🔗 https://lnkd.in/g6xn2K3g Learning Journey: 🔹 Today’s problem focused on transforming a binary tree into a flattened linked list in-place. 🔹 I used an iterative approach, modifying pointers while traversing the tree. 🔹 For each node with a left subtree, I found the rightmost node of that subtree and connected it to the current node’s right subtree. 🔹 Then, I moved the left subtree to the right and continued traversal. Concepts Used: 🔹 Binary Trees 🔹 Tree Traversal 🔹 Pointer Manipulation 🔹 In-place Modification Key Insight: 🔹 Tree restructuring problems often rely on careful pointer adjustments. 🔹 Finding the predecessor (rightmost node of left subtree) helps preserve traversal order. 🔹 Iterative solutions can avoid recursion and reduce extra space usage. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

✅ Day 53 of 100 Days LeetCode Challenge Problem: 🔹 #191 – Number of 1 Bits 🔗 https://lnkd.in/gZPa-tQf Learning Journey: 🔹 Today’s problem focused on counting the number of set bits (1s) in the binary representation of an integer. 🔹 I converted the number to its binary form and iterated through the string representation. 🔹 By counting occurrences of '1', I determined the Hamming weight of the number. 🔹 This approach is simple and clear for understanding bit representation. Concepts Used: 🔹 Bit Manipulation 🔹 Binary Representation 🔹 String Conversion 🔹 Counting Technique Key Insight: 🔹 Every integer can be analyzed at the bit level for efficient computation. 🔹 Converting to binary provides an intuitive way to visualize set bits. 🔹 Bit manipulation problems often have multiple optimized approaches beyond basic counting. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity