Solved 9. Palindrome Number with math and logic

Another LeetCode problem solved: 507. Perfect Number. While the standard approach involves calculating divisors , I took a step back and looked at the constraints. For the range 1<num<10^8, there are only a handful of known Perfect Numbers (6, 28, 496...). Leveraging this mathematical insight allowed for an O(1) time complexity lookup, resulting in a 0 ms runtime and a 100% beat! This is a great reminder that efficient coding often starts with mathematical analysis, not just algorithm design. Have you ever found a great mathematical shortcut like this in a coding problem? Share your insights! 👇 #LeetCode #ProblemSolving #Algorithms #Optimization #Mathematics #Python #Coding

📌 Day 9 of My #50DaysOfPython Challenge 🐍 🔹 Task: Find the GCD (Greatest Common Divisor) using Recursion Today I explored one of the most elegant mathematical algorithms — the Euclidean Algorithm — to find the GCD (Greatest Common Divisor) of two numbers. This algorithm shows how mathematics + recursion = pure logic power 💡 🧠 What I Learned: The concept of GCD (HCF) — the largest number that divides both numbers. The Euclidean Algorithm formula: GCD(a,b)=GCD(b,a%b) This task deepened my understanding of how recursion works in mathematical logic — and how complex problems can be solved with just a few lines of clean Python code 💻 #Python #CodingChallenge #Recursion #50DaysOfPython #ProblemSolving #LearningJourney

Today, I experimented with a Column Transformation inside my notebook: 𝐓𝐢𝐦𝐞-𝐂𝐨𝐧𝐬𝐮𝐦𝐢𝐧𝐠 𝐀𝐩𝐩𝐫𝐨𝐚𝐜𝐡 ▪ Each step is done separately: ➤ Scaling numeric columns. ➤ Imputing missing values. ➤ One-hot encoding categorical features. ➤ Ordinal encoding, etc. You have to apply each transformation individually, which takes more time and can get messy. 𝐁𝐞𝐬𝐭 𝐀𝐩𝐩𝐫𝐨𝐚𝐜𝐡 ▪ Use a ColumnTransformer to handle everything in one single pipeline: ➤ Impute missing values. ➤ Apply ordinal encoding. ➤ Apply one-hot encoding. ➤ Keep other columns as-is. All transformations happen in one step, making it clean, fast, and error-free. #MachineLearning #DataScience #ColumnTransformer #sklearn #Python #HopeToSkill #LearningJourney

𝗗𝗮𝘆 𝟯𝟲 𝗼𝗳 #𝟭𝟴𝟬𝗗𝗮𝘆𝘀𝗢𝗳𝗖𝗼𝗱𝗲 Today, I solved 𝗦𝗲𝗮𝗿𝗰𝗵 𝗜𝗻𝘀𝗲𝗿𝘁 𝗣𝗼𝘀𝗶𝘁𝗶𝗼𝗻 — a practical variation of binary search. The goal was to find the index of a target in a sorted array, or the position where it should be inserted to maintain order. Using binary search, I efficiently located the correct spot in O(log n) time. The key was to track the first position where the element is greater than or equal to the target — which is exactly the insert position if the target isn’t found. This is a great example of how small tweaks to a classic algorithm can solve new problems elegantly. A useful technique for search, insertion, and maintaining sorted data dynamically! #Python #Algorithms #BinarySearch #LeetCode #Coding #ProblemSolving

Today's LeetCode problem was the foundational 509. Fibonacci Number. While there are faster ways to solve this, I focused on implementing the classic recursive solution. It's such a fundamental concept to understand, as it directly mirrors the mathematical definition: $F(n) = F(n-1) + F(n-2)$. It's a great reminder that coding is often about translating mathematical logic directly into code. The pursuit of efficiency (like using memoization next!) never stops, but understanding the basics is paramount. #LeetCode #Recursion #DSA #Algorithms #Python #ComputerScience

Day 13 of #100DaysOfLeetCode Problem: 88. Merge Sorted Array Category: Arrays / Sorting / Two Pointers Today’s challenge focused on merging two sorted arrays into one, maintaining the sorted order. It’s a simple yet powerful problem that tests your understanding of array indices, merging logic, and in-place updates. 🧠 Key Learnings: Extended the first array by adding elements from the second, then sorted the combined list. Reinforced the importance of efficient merging techniques for sorted sequences. Understood how in-place operations can reduce memory usage in practical scenarios. Strengthened logic building around sorting fundamentals and index-based insertion. 🎯 Takeaway: Even simple array problems help build strong fundamentals in sorting and data manipulation — the key to mastering larger algorithmic challenges. #LeetCode #100DaysOfCode #ProblemSolving #CodingJourney #Arrays #Sorting #Python #AIEngineer #Consistency

Day 5 of #100DaysOfLeetCode Problem: 54. Spiral Matrix Category: Arrays / Matrix Traversal Today’s challenge focused on traversing a 2D matrix in spiral order and returning all elements in that pattern. This problem was really fun to solve because it required handling multiple edge cases while maintaining clean traversal logic. 🧠 Key Learnings: Used the concept of repeatedly peeling off the outer layer of the matrix. Traversed top row → right column → bottom row → left column in sequence. Understood the importance of checking matrix boundaries after each step to avoid index errors. Improved logical thinking for problems involving nested data structures. 🎯 Takeaway: Matrix traversal problems are all about maintaining control over direction and boundaries — once that’s handled, the logic flows smoothly. #LeetCode #100DaysOfCode #ProblemSolving #CodingJourney #Matrix #Arrays #Python #AIEngineer #Consistency