LeetCode 516: Longest Palindromic Subsequence in Python

LeetCode Problem 83: Given the head of a sorted linked list, delete all duplicates such that each element appears only once. Return the linked list sorted as well. The below implementation in Python successfully resolves this in time complexity of O(n) where n is length of the list with constant space complexity. The approach is simple, handle the base case first like list having 0 or 1 number of nodes and then write the logic of handling lists of length greater than one. Maintain two pointers, one to keep track of present node and other to keep track of previous node. Check if the value of both nodes match or not, if match update the pointing of previous node, point its next to the present.next. #LeetCode #LinkedList #Python #CompetitiveProgramming #Algorithms #DataStructures #ProblemSolving

LeetCode Problem 1980: "Find Unique Binary String": Given an array of strings nums containing n unique binary strings each of length n, return a binary string of length n that does not appear in nums. If there are multiple answers, you may return any of them. The below implementation in Python correctly resolves this using bit manipulation functions and loops. #Python #LeetCode #Strings #BitManipulation #CompetitiveProgramming #Algorithms #DataStructures #ProblemSolving

LeetCode Problem 1461: "Check if a binary string contains all binary codes of size k": Given a binary string s and an integer k, return true if every binary code of length k is a substring of s. Otherwise, return false. Approach: I simply used a sliding window and a hash map where hash map stores the seen substrings of size k. Two pointers keep track of each substring of size k. A count variable is initialized to 0 which is incremented each time when a unique unseen substring of size k is seen, if this count reaches the max possible number of unique binary codes of size k (i.e. 2^k) the function returns True else False. #LeetCode #Python #BitManipulation #Strings #SlidingWindow #DataStructures #Algorithms #CompetitiveProgramming #ProblemSolving #OptimalSolution

Day 6 of #LearnInPublic Today I worked on the problem: First Non-Repeating Element in an Array. I implemented two approaches in Python: 1️⃣ Hash Map Approach (Using defaultdict) • Count frequency of each element • Traverse again to find the first element with frequency = 1 Time Complexity: O(n) Space Complexity: O(n) 2️⃣ Brute Force Approach • Compare every element with the rest of the array Time Complexity: O(n²) Space Complexity: O(1) Key takeaway: Using a hash map trades extra space for a significant improvement in time complexity. Small daily improvements compound over time. #Python #DataStructures #Algorithms #LearnInPublic #CodingJourney

LeetCode #226 – Invert Binary Tree | Python Implementation I implemented a recursive DFS approach that swaps left and right children at every node. Core Insight: Tree inversion is distributive — inverting a tree equals swapping its root's children and inverting each subtree independently. Recursion handles this naturally in O(n) time. Time: O(n) | Space: O(h) where h = tree height (recursion stack) #LeetCode #DataStructures #Python #BinaryTree #Recursion #DFS #CodingInterview #SoftwareEngineering

🚀 Day 56 — LeetCode 451: Sort Characters by Frequency using HashMap + Sorting. 💡 Key Learnings: • Counting character frequency using dictionary • Custom sorting with key=lambda • Efficient string building using "".join() • Understanding time vs space complexity trade-offs ⏱️ Complexity: Time — O(n + k log k) Space — O(k) #Day56 #LeetCode #Python #DataStructures #DSA #CodingJourney #ProblemSolving

Learn in Public – Day 13 Today I practiced implementing the Armstrong Number problem in Python using two different approaches. 🔹 Approach 1: Converting the number to a string and calculating the power of each digit. 🔹 Approach 2: A more mathematical approach using functions like order() and a recursive power() function. Key learnings from today: • How Armstrong numbers work mathematically • Practicing recursion through a custom power function • Working with digits using modulus and integer division • Writing cleaner modular functions Example: 153 → 1³ + 5³ + 3³ = 153 Consistency > Motivation. #LearnInPublic #Python #CodingPractice #ProblemSolving #100DaysOfCode

Binary search is a pretty simple algorithm, but it can sometimes cause problems, especially with off-by-one index errors. If possible, we should use the language's built-in methods, for example, `bisect` in Python. However, in some cases, we have to implement it ourselves. While an iterative approach is pretty straightforward, sometimes switching to recursion would produce simpler code. Thus, if we already use additional space, and the call stack won't affect the space complexity, it's reasonable to use recursion. The post: https://lnkd.in/dTttqaCW The problem: https://lnkd.in/dTCzj5Qc #LeetCode #DSATips #DSA #ThinkDSA #ProblemSolving

🚀 Day 20 of #100DaysOfLeetCode 📌 Problem Solved: Search Insert Position 🧠 Topic: Binary Search Your approach: Classic binary search If found → return index If not found → return left (correct insert position) Why returning left works: At the loop end, left points to the smallest index where the target can go while keeping the array sorted. ⏱ Time Complexity: O(log n) 💾 Space Complexity: O(1) This is a solid DSA base already. Keep stacking days like this 🔥 #day20 #100daysofLeetCode #DSA #Python #BinarySearch #ConsistencyWins

You can fit the most common Bayesian regression models in Python using a consistent syntax (similar to brms in R) using the bambi package. It utilizes PyMC to do the simulations. It's remarkably easy and straightforward to use - you just adjust the family name to the right model type. Here are a few examples. More instructions are available here: https://lnkd.in/eGSG3-Bk #statistics #datascience #analytics #rstats #python #peopleanalytics #technology #ai