DAY 102 Problem: LeetCode 1320 (Hard) Min total distance to type a word with 2 fingers on a 5x6 keyboard. DP state: (index, other finger pos) → 27 states. n≤300, O(n*27^2) works. #LeetCode #DynamicProgramming #Coding

Day 33 of #100DaysOfCode 🚀 Solved LeetCode 198 & 213 (House Robber series). Practiced recursion → memoization → optimized DP and learned to handle circular cases by splitting into linear ones. Key takeaway: focus on states & transitions. #DSA #DynamicProgramming #LeetCode

🚀 Day 37 of #100DaysOfCode Challenge Today’s focus: Dynamic Programming 💡 Learning under the guidance of Rohit Negi (Coder Army) and Aditya Tandon. #Day37 #DynamicProgramming #CodingJourney #100DaysChallenge #Java #ProblemSolving #TechLearning

Day 176 of my DSA journey Solved 3 DP problems today: • Word Break • Coin Change II • Unique Paths DP is starting to feel less scary and more like pattern recognition now. Consistency > motivation 💯 #DSA #DynamicProgramming #CodingJourney #100DaysOfCode #KeepBuilding

🚀 **Saturday Questions ❓ — 11-04-2026** #DynamicProgramming Dynamic Programming is one of the most important skills in technical interviews. 👉 **Break the problem into smaller subproblems** 👉 **Store results to avoid recomputation** learnwithchampak.live/2026/04/saturd…

First in my bloodline grinding "Best Time to Buy and Sell Stock II", still clueless after endless dry runs, all while AI might make DSA irrelevant 🤸‍♂️🥀😭 #DynamicProgramming #imdone

🚀 Day 36 – Dynamic Programming Journey for top tech companies like: Meta Google Amazon Microsoft Salesforce Consistency is the key 🔑 — one step every day! #Day36 #100DaysOfCode #DynamicProgramming #CodingJourney #DSA #Consistency #Learning #TechCareers

Started learning Dynamic Programming 🚀 Explored Fibonacci using Memoization (recursion) & Tabulation (loops), and applied the same logic to solve Climbing Stairs (LeetCode #70) 🪜 #DSA #DynamicProgramming #LeetCode

Day - 35 🚀 Dynamic Programming (Medium Level) Continuing my journey of the 100 Days Challenge 💪 Companies like: Google | Microsoft | Walmart | Goldman Sachs | Facebook #Day35 #DynamicProgramming #100DaysChallenge #DSA #CodingJourney #Consistency

If you are going to study Dynamic Programming(DP) then refer to Aditya Verma's youtube lectures His videos are gem ✨ #dynamicprogramming #dp #dsa #algorithms #web3

Day - 34 🚀 Started Dynamic Programming today 🔥 Problem: Maximum Length of a Concatenated String with Unique Characters (Leetcode 1239) 100 Days Consistency Challenge 💪 #Day34 #DP #DynamicProgramming✅ #100DaysChallenge #CodingJourney

Day 75 | DSA Problem: Longest Common Subsequence • Find LCS of two strings • DP: dp[i][j]=1+dp[i-1][j-1] if match, else max(dp[i-1][j],dp[i][j-1]) • Time: O(m×n), Space: O(m×n) #Java #Leetcode #DynamicProgramming

🚀 Day - 33 Greedy Algorithm ❌ → Dynamic Programming ✅ Today marks the end of Greedy Algorithms and the beginning of Dynamic Programming (DP) 💡 Solved: Continuing the 100 Days Challenge with consistency 🔥 #Day33 #DP #DynamicProgramming✅ #100DaysChallenge #CodingJourney

DP is hard, isn't it ?🥲 Solved some problem after struggling alot as for now my dp mindset is have to be intialized inside my brain.😁 will try to do more of it. Any Tips for dynamic Programming :) #LeetCode #DynamicProgramming #DSA

Day 172 – DP Revision Revised: 🏠 House Robber 🏠 House Robber II 💰 Coin Change #100DaysOfDSA #DynamicProgramming #CodingQuiz

Day 74 | DSA Problem: Longest Increasing Subsequence • Find longest strictly increasing subsequence • DP: dp[i] = max(dp[j]+1) for j<i • Initialize dp[i]=1 for all • Track max length while iterating • Time: O(n²), Space: O(n) #Java #Leetcode #DynamicProgramming

Day 49 🚀 #GeekStreak60 Solved the Target Sum problem using a clever DP transformation. Converted it into a Subset Sum count → efficient over brute force 💡 Consistency > intensity. #DSA #DynamicProgramming #CodingJourney #npci @geeksforgeeks @NPCI_NPCI

Stop trying to brute force signs (+/-) in the Target Sum problem. 🛑 It’s just a math trick! By splitting the array into two subsets (S_1 and S_2), the problem simplifies to: S_1 - S_2 = target S_1 = (totalSum+ target) / 2 #Day155 #DynamicProgramming #CPP

Day 73 | DSA Problem: Maximum Product Subarray • Track max & min (handle negatives) • Swap effect when number is negative • max = max(curr, currmax, currmin) • Update result with max • Time: O(n), Space: O(1) #Java #Leetcode #DynamicProgramming

Day 15 of POTD streak 🔥 Solved: Painting Fence Used DP with two states (same & different colors) → Built recurrence for valid combinations Nice problem to understand state transitions #POTD #DSA #DynamicProgramming #CodingJourney