📅 Day 63 of #100DaysOfCode Today’s challenge was all about matrix manipulation in C! I built a simple yet powerful program that: ✅ Accepts a 3×3 matrix from user input ✅ Displays the original matrix in formatted output ✅ Computes and prints its transpose by swapping rows and columns This exercise reinforced my understanding of 2D arrays, nested loops, and matrix operations—core concepts in both math and programming. It’s a great stepping stone toward more advanced topics like matrix multiplication and determinants. Let’s keep the momentum going! 🚀 #CProgramming #MatrixTranspose #CodeNewbie #LearnToCode #DailyCoding #CodingChallenge #TechJourney #100DaysChallenge #CodeWithAnmol #VisualCoding #2DArrays #TransposeMatrix #Day63

🌀 Day 48 of #100DaysOfCode Today I tackled a visually satisfying challenge—generating a Spiral Matrix in C! The program dynamically fills an n x n matrix in a clockwise spiral pattern using boundary pointers (top, bottom, left, right) and a value counter. It’s a great exercise in mastering loop control and matrix traversal. ✨ Highlights: Clean logic using layered loops Dynamic matrix filling without recursion Output beautifully formatted for clarity 🔢 Input: Matrix size n (1–20) 📤 Output: Spiral matrix printed with aligned values 📌 Perfect for practicing: Array manipulation Loop boundaries Visual formatting in C #CProgramming #Day48 #CodingChallenge #LearnByDoing #VisualAlgorithms #CodeCraft

Must-Know Algorithms for Every Programmer! Whether you’re into Data Structures, Graphs, or Optimization — mastering algorithms is the secret to writing efficient code Key Topics: Stack, Queue, BST, Hashing DFS & BFS Dijkstra & Bellman-Ford Dynamic & Greedy Algorithms Pattern Matching Techniques Level up your problem-solving skills today! 👉 https://lnkd.in/gxYyJQAU #Programming #Algorithms #DataStructures #CodingSkills #SoftwareDevelopment #LearnToCode #DigitalEarnSolution #TechLearning

🚀 Algorithm Challenge #15 🧠 Problem Title: Calculate the area of a rectangle based on user input for its length and width. ✅ Language Used: C++ 💡 What it covers: Working with user inputs Performing arithmetic operations (multiplication) Using variables and basic math formulas Understanding how to apply logic from geometry in programming 📂 GitHub Repo: 🔗 https://lnkd.in/dGe3ZbxK 📝 Short Description: In this challenge, I wrote a simple C++ program that asks the user to enter the length and width of a rectangle, then calculates and displays the area. It’s one of the foundational examples that combines mathematical formulas with programming logic — a great step toward building more practical problem-solving skills. 💬 Feedback Welcome! I’d love to hear your thoughts or suggestions for expanding this example — maybe by adding perimeter calculation or input validation next time 👀 🔁 Stay tuned for Challenge #16 coming soon! #Cpp #Programming #CodingChallenge #Algorithms #ProblemSolving  #MathInProgramming #Geometry #LearnToCode #CodeNewbie #SoftwareDevelopment #BuildInPublic #CppProgramming #TechLearning #LogicalThinking  #100DaysOfCode #LinkedInLearning

🌟 Day 10 of #100DaysOfCoding Today’s challenge was the “Missing Number” problem — a neat exercise in mathematical reasoning and array manipulation. The task: Given an array containing n distinct numbers taken from 0 to n, find the one number that’s missing. Instead of using extra space or sorting, I applied a simple mathematical approach — leveraging the formula for the sum of the first n natural numbers. By comparing the expected sum to the actual sum of elements, the missing number reveals itself instantly! 💡 Key takeaway: Sometimes, the most elegant solutions come from combining math with programming logic. #100DaysOfCode #Day10 #CodingChallenge #ProblemSolving #Algorithms #DataStructures #LearnInPublic #CPP #KeepCoding #CodeNewbie

🔥 Day 9 of #100DaysOfCoding Today I explored another interesting concept — finding the maximum subarray sum using Kadane’s Algorithm. This problem taught me how powerful dynamic programming can be when solving optimization challenges. Instead of checking every possible subarray (which would be too slow), Kadane’s Algorithm efficiently finds the answer in just one pass through the array! 💡 Key takeaway: Optimization is not always about doing more; it’s often about doing smarter. #100DaysOfCode #Day9 #CodingChallenge #ProblemSolving #Algorithms #DynamicProgramming #DataStructures #LearnInPublic #KeepCoding #CodeNewbie

Hey folks — it’s Reyhaneh from Freyja Channel, back again to make Fortran look way cooler than your grandpa remembers. 👩💻✨ In Episode 20 of our Fortran for Numerical Computing series, we’re diving into one of the classics — the DO WHILE loop. Yep, that little structure that keeps your code running while your logic still makes sense (and doesn’t crash your solver 😅). If you’re leveling up your Fortran game or just love clean, efficient loops — this one’s for you. 🎥 Watch here: https://lnkd.in/dEzbpzhW Let’s make those numerical computations sing. 🎶💻 #Fortran #NumericalComputing #ProgrammingEducation #CodeWithFreyja #STEM #WomenInTech #FortranTutorial #LearnToCode #ScientificComputing #CodingCommunity

🚀 Day 67 | Math & Dynamic Programming Insights Today’s challenge was all about maximizing product through intelligent partitioning — a perfect mix of mathematical intuition and dynamic programming. 🧩 Problem Solved: 343. Integer Break • Approach: Used dynamic programming to compute the maximum product by breaking n into smaller integers, or derived the math-based insight that splitting into 3s gives the optimal product. • Insight: Not every optimization needs brute force — sometimes, number patterns reveal the most efficient path. ✨ Key Takeaway: Mathematics and programming go hand in hand — understanding the underlying formula often leads to cleaner and faster solutions. 📚 Topics: Math · Dynamic Programming · Optimization 💻 Platform: LeetCode #DSA #LeetCode #ProblemSolving #DailyCoding #DynamicProgramming #Math #Consistency

🚀 Day 65 | Math Patterns & Pascal’s Logic Today’s problem revisited one of the most elegant mathematical structures — Pascal’s Triangle — focusing on generating a specific row efficiently. 🧩 Problem Solved: 119. Pascal’s Triangle II • Approach: Built the row iteratively using the relationship row[i] = row[i-1] * (n - i + 1) / i, avoiding full triangle generation. • Insight: Recognizing combinatorial patterns transforms nested loops into simple mathematical formulas. ✨ Key Takeaway: Efficiency often comes from understanding the math beneath the pattern — logic over loops. 📚 Topics: Math · Dynamic Programming · Combinatorics 💻 Platform: LeetCode #DSA #LeetCode #ProblemSolving #DailyCoding #Math #DynamicProgramming #Consistency

📊 LeetCode #3318. The X-Sum Problem of All K-Long Subarrays Today I worked on an interesting frequency-driven sliding window problem: Find X-Sum of All K-Long Subarrays. The task involves evaluating each subarray of length k and computing its x-sum, which is determined by retaining only the x most frequent elements. In case of ties, the element with the larger value is prioritized. Once filtered, the sum of the selected elements forms the final result for that window. This problem stands out because it blends two ideas: - Maintaining dynamic frequencies while the window slides. - Selecting elements based on a custom ranking rule combining frequency and value. Even with small constraints, it emphasizes the importance of correctly managing counts and ordering logic. It's a clean example of how sliding window techniques can integrate with priority based selection to build efficient solutions. ⏱ Time Complexity: O(n × log n) 🧠 Space Complexity: O(n) #LeetCode #SlidingWindow #ProblemSolving #Programming #Algorithms #DataStructures #Python #SoftwareEngineering #CodingPractice #TechLearning