#dynamicprogramming resultados da pesquisa
DSA is the most important for anyone learning programming But not easy to master. I made a complete Data Structure and algorithms Handwritten Note. ( Worth $45) But, for 24 hours, It's 100% FREE. To get it, just: → Like & Retweet → Reply "DSA" → Follow me (so I can DM)

7 Reddit communities to learn AI better than most paid courses:

Dynamic Programming was HARD until I Learned these 20 Problems and Patterns: 1. Fibonacci Sequence 2. Kadane's Algorithm 3. 0/1 Knapsack 4. Unbounded Knapsack 5. Longest Common Subsequence (LCS) 6. Longest Increasing Subsequence (LIS) 7. Palindromic Subsequence 8. Edit Distance…

🧩 LeetCode 300: Longest Increasing Subsequence 🔑 Idea → DP + Binary Search ⚡ Approach → Recursion + Memoization → Tabulation → O(n log n) 💡 Learning → Optimizing step by step shows the true power of DP 🚀 #LeetCode #DynamicProgramming #DSA #100DaysOfCode #ProblemSolving

Coding was never really about writing code. It was about breaking a problem into steps, imagining the edge cases, and knowing where trade-offs live. AI just took away the boring part. What’s left is the real work: thinking clearly.
Most agents today are shallow. They easily break down on long, multi-step problems (e.g., deep research or agentic coding). That’s changing fast! We’re entering the era of "Deep Agents", systems that strategically plan, remember, and delegate intelligently for solving very…

Learning in public #Day35 1. DSA - 4 questions on DP on subsets and subsequences, Leetcode 2035(hard q). less productive day :( #DynamicProgramming

Hi @RichardSSutton, I’m trying to understand how Dynamic Programming (DP) fits into Reinforcement Learning. My professor mentioned that DP methods like policy iteration and value iteration are used in RL even when model environment is not known

🚀 DSA Series #8 — Dynamic Programming 🧠 DP isn’t just recursion — it’s recursion with memory. Once it clicks, you stop solving problems and start optimizing them. 👇 Read here 🔗 medium.com/@vinayakmalviy… #DSA #DynamicProgramming #ProblemSolving #CodingJourney
Print Longest Increasing Subsequence 1️⃣ Build dp - length of LIS at each index 2️⃣ Use hash - track predecessors to backtrack 3️⃣ Find LIS end, trace back, reverse - actual subsequence #DynamicProgramming #100DaysOfCode #LearnInPublic #Coding #DSA

🗓️23 August 2025 ✅ Solved: 🔹 Matrix Chain Multiplication using Memoization 🔹 Matrix Chain Multiplication using Tabulation 💻learned about cloning, exception handling, collections framework, and enums - completely revised OOPs #DynamicProgramming #Java #oops #CodingJourney



#DynamicProgramming. started today learn 3 approaches to tackle after recursion m1->top to down approach m2->tabulation OR down to UP approach m3->Space Optimisation approach(m2 ka pattern dekho kuchh milega wahi m3 hai)




#Day83 Solved Coin Change II 💰using Tabulation DP 🔹Transition: if coins[i-1] <= j: dp[i][j] = dp[i][j - coins[i-1]] + dp[i-1][j] else → exclude: dp[i][j] = dp[i-1][j] Pattern: Count of subsets with repetition allowed #DynamicProgramming #LeetCode #100DaysOfCode #DSA #tech
![singh_jayraj_05's tweet image. #Day83
Solved Coin Change II 💰using Tabulation DP
🔹Transition:
if coins[i-1] &lt;= j:
dp[i][j] = dp[i][j - coins[i-1]] + dp[i-1][j]
else → exclude: dp[i][j] = dp[i-1][j]
Pattern: Count of subsets with repetition allowed
#DynamicProgramming #LeetCode #100DaysOfCode #DSA #tech](https://pbs.twimg.com/media/GzmxUK_bEAATVw5.jpg)
🚀 Day 138: Matrix Chain Multiplication Solved using DP + Optimal Parenthesization 💡 ✔️ Recurrence: dp[i][j] = min(dp[i][k] + dp[k+1][j] + arr[i-1]*arr[k]*arr[j]) ⏱️ O(n³) time, O(n²) space #DynamicProgramming #MCM #gfg160 #100DaysOfCode #geekstreak2025 @geeksforgeeks
![YojitKataria's tweet image. 🚀 Day 138: Matrix Chain Multiplication
Solved using DP + Optimal Parenthesization 💡
✔️ Recurrence: dp[i][j] = min(dp[i][k] + dp[k+1][j] + arr[i-1]*arr[k]*arr[j])
⏱️ O(n³) time, O(n²) space
#DynamicProgramming #MCM #gfg160 #100DaysOfCode #geekstreak2025
@geeksforgeeks](https://pbs.twimg.com/media/GypdFdvX0AMYtqc.jpg)
![YojitKataria's tweet image. 🚀 Day 138: Matrix Chain Multiplication
Solved using DP + Optimal Parenthesization 💡
✔️ Recurrence: dp[i][j] = min(dp[i][k] + dp[k+1][j] + arr[i-1]*arr[k]*arr[j])
⏱️ O(n³) time, O(n²) space
#DynamicProgramming #MCM #gfg160 #100DaysOfCode #geekstreak2025
@geeksforgeeks](https://pbs.twimg.com/media/Gypld7BX0AEVbpn.jpg)
📅20 August 2025 ✅ Solved: 🔹 Longest Increasing Subsequence using Memoization, Tabulation & Space Optimization 🔹 Print Longest Increasing Subsequence 💻 Revised Generics and Built a Custom ArrayList in Java #100DaysOfCode #DynamicProgramming #Java #DSA #CodingJourney #LeetCode




🧩 LeetCode 1547: Minimum Cost to Cut a Stick 🔑 Idea → Interval #DP + Divide & Conquer ⚡ Approach → Recursive splits + memoization 💡 Learning → DP on partitions = optimal cuts + state reuse 🚀 #LeetCode #DynamicProgramming #Algorithms #DSA #ProblemSolving #100DaysOfCode

Leetcode 300. Longest Increasing Subsequence 1️⃣ Naive recursion: take/skip - exponential 2️⃣ Add "last chosen index" - valid subsequences 3️⃣ Memoize (ind,last+1) Brute -> State -> DP #LearnInPublic #100DaysOfCode #DynamicProgramming #LeetCode

🚀 DSA Series #8 — Dynamic Programming 🧠 DP isn’t just recursion — it’s recursion with memory. Once it clicks, you stop solving problems and start optimizing them. 👇 Read here 🔗 medium.com/@vinayakmalviy… #DSA #DynamicProgramming #ProblemSolving #CodingJourney
DP Problem Set Complete 10 DP problems on LeetCode. Focus on identifying DP patterns and building solutions incrementally. #dynamicprogramming #dp #day25
Day 18/100 💻#100DaysOfCode 🧩 DSA: Solved Unique Paths & Unique Paths II Practiced Memoization, Tabulation, & Space Optimization in DP ☁️ AWS: Covered AWS Global Infrastructure IAM & Root User Security Hosted an Employee Directory App on AWS 🚀 #DynamicProgramming #AWS



Day 23 of #LeetCodeJourney 🚀 Solved 3539. Find Sum of Array Product of Magical Sequences (Hard) 💫 This one was really tough 😮💨 — had to refer the solution to understand the recursive DP with carry propagation and combinatorics. #LeetCode #DynamicProgramming #100DaysOfCode
🔥 LeetCode Daily Challenge — Accepted! 🏆 Beats 99.36% in runtime (422 ms) Cracked this one using recursive thinking + memoization, smart combinatorics, and modular arithmetic. 💡 Runtime: 422 ms 💾 Memory: 34 MB #LeetCode #Python #DynamicProgramming #Coding #Day44

Day 15/100 ✅ LeetCode POTD solved! Am I the only one who thinks DP questions require you to think like this?! 😂 Streak: 🔥 73 days strong! #LeetCode #100DaysOfCode #DynamicProgramming
Finally solved @LeetCode 3539 (Hard) after 7 attempts 😤 It took me around 1 hour 37 mins to solve it. This one was intense . #LeetCode #DynamicProgramming #Coding #DSA #HardProblem

🚀 Day 444 of Code 🚀 Solved : ✅ 3186. Maximum Total Damage With Spell Casting #Day444 #LeetCode #DynamicProgramming #ProblemSolving #Algorithms #CodingJourney #DSA #Optimization #100DaysOfCode


Day 17/100 💻#100DaysOfCode 🧩 Solved: Frog Jump Frog Jump with K Distances Maximum Sum of Non-Adjacent Elements House Robber #DSA #DynamicProgramming #AWS #CloudComputing #100DaysChallenge #CodingJourney




(Open Access) Dynamic Programming and Bayesian Inference, Concepts and Applications: freecomputerbooks.com/Dynamic-Progra… Look for "Read and Download Links" section to download. Follow me if you like #DynamicProgramming #Bayesian #BayesianInference #Statistics #LinearProgramming #Optimization

Day 51 #LeetCode ⚡ Solved #POTD 3186 Maximum Total Damage With Spell Casting 🪄 👉 Used frequency map + DP on sorted unique powers 👉 Careful handling of adjacent/interfering values (±1, ±2 range) ⏱ O(n log n) | 💾 O(n) #DynamicProgramming #LeetCode #100DaysOfCode

🧠 LeetCode — 3186. Maximum Total Damage With Spell Casting ⏱️ Solved in: ⌛ 16.39 mins 💡 Approach: DP + Binary Search ⏳ Time Complexity: O(n log n) 💾 Space Complexity: O(n) 📅Date :- 11/10/2025 #LeetCode #DynamicProgramming #BinarySearch #POTD #DSA #Coding #100DaysOfCode

Day 74 – LeetCode Challenge Problem: 3147. Taking Maximum Energy From the Mystic Dungeon ⚡ #Day74 #LeetCode #DynamicProgramming #100DaysOfCode #CodingJourney #CodeNewbie #DSA #Cplusplus #ProblemSolving #LeetCodeDaily #SoftwareEngineering #TechTwitter #CodeLife #Programmer

⚔️ LeetCode Daily: Maximum Energy from Mystic Dungeon ✅ Backward DP FTW! Process right-to-left, accumulate energy from k-jumps ahead. ⚡ O(n) single pass 🎯 Suffix sum with jumps 💡 Any start position valid #LeetCode #CPlusPlus #DynamicProgramming #100DaysOfCode

Day 16/100 💻 #100DaysOfCode 🧠 Solved: Counting Bits Min Cost Climbing Stairs Is Subsequence Each problem, one step closer to mastering patterns & optimization ⚡ #DSA #DynamicProgramming #CodingJourney #100DaysChallenge



🧠 LeetCode POTD — 3147. Taking Maximum Energy From the Mystic Dungeon ⏱️Solved in: ⌛ 11.28 mins 💡Approach: 1D Dynamic Programming (Bottom-Up) ⏳Time Complexity: O(n) 💾Space Complexity: O(n) 📅Date - 10/10/2025 #LeetCode #potd #DynamicProgramming #DSA #Coding #100DaysOfCode




Day 50 #LeetCode ⚡ Half-century streak! 🥳 Solved 3147. Taking Maximum Energy From the Mystic Dungeon 👉 Used modular DP (index % k) to track energy paths 👉 Reverse accumulation for optimal jumps ⚙️ O(n) time | O(k) space #100DaysOfCode #DynamicProgramming #LeetCode #grind

Day 12 of #100DaysOfCode Tackled LeetCode 3147 — Taking Maximum Energy From the Mystic Dungeon ⚔️ A neat little DP problem — just a stride-based recurrence, clean and satisfying! Feeling good about today’s progress 💪 #LeetCode #DynamicProgramming #CodingJourney

🧵 LeetCode 75 — Day 10: Tribonacci Number The Tribonacci sequence extends Fibonacci — each term is the sum of the previous three. Given n, return Tn. #LeetCode #DynamicProgramming #Java #100DaysOfCode
🧩 LeetCode 300: Longest Increasing Subsequence 🔑 Idea → DP + Binary Search ⚡ Approach → Recursion + Memoization → Tabulation → O(n log n) 💡 Learning → Optimizing step by step shows the true power of DP 🚀 #LeetCode #DynamicProgramming #DSA #100DaysOfCode #ProblemSolving

#Day83 Solved Coin Change II 💰using Tabulation DP 🔹Transition: if coins[i-1] <= j: dp[i][j] = dp[i][j - coins[i-1]] + dp[i-1][j] else → exclude: dp[i][j] = dp[i-1][j] Pattern: Count of subsets with repetition allowed #DynamicProgramming #LeetCode #100DaysOfCode #DSA #tech
![singh_jayraj_05's tweet image. #Day83
Solved Coin Change II 💰using Tabulation DP
🔹Transition:
if coins[i-1] &lt;= j:
dp[i][j] = dp[i][j - coins[i-1]] + dp[i-1][j]
else → exclude: dp[i][j] = dp[i-1][j]
Pattern: Count of subsets with repetition allowed
#DynamicProgramming #LeetCode #100DaysOfCode #DSA #tech](https://pbs.twimg.com/media/GzmxUK_bEAATVw5.jpg)
Learning in public #Day35 1. DSA - 4 questions on DP on subsets and subsequences, Leetcode 2035(hard q). less productive day :( #DynamicProgramming

🗓️23 August 2025 ✅ Solved: 🔹 Matrix Chain Multiplication using Memoization 🔹 Matrix Chain Multiplication using Tabulation 💻learned about cloning, exception handling, collections framework, and enums - completely revised OOPs #DynamicProgramming #Java #oops #CodingJourney



#DynamicProgramming. started today learn 3 approaches to tackle after recursion m1->top to down approach m2->tabulation OR down to UP approach m3->Space Optimisation approach(m2 ka pattern dekho kuchh milega wahi m3 hai)




🔺Day 56/100 DSA Solved Triangle Minimum Path Sum using bottom-up DP. Pick the smaller of the two paths below at each step → final answer at the top! 💡 #100DaysOfCode #DSA #DynamicProgramming

Print Longest Increasing Subsequence 1️⃣ Build dp - length of LIS at each index 2️⃣ Use hash - track predecessors to backtrack 3️⃣ Find LIS end, trace back, reverse - actual subsequence #DynamicProgramming #100DaysOfCode #LearnInPublic #Coding #DSA

🚀Day 28 of DSA Journey: Solved DP Question #DSA #CodingJourney #DynamicProgramming #100DaysOfCode Maximum sum of non-adjacent elements

🧩 LeetCode 1547: Minimum Cost to Cut a Stick 🔑 Idea → Interval #DP + Divide & Conquer ⚡ Approach → Recursive splits + memoization 💡 Learning → DP on partitions = optimal cuts + state reuse 🚀 #LeetCode #DynamicProgramming #Algorithms #DSA #ProblemSolving #100DaysOfCode

🚀 Day 138: Matrix Chain Multiplication Solved using DP + Optimal Parenthesization 💡 ✔️ Recurrence: dp[i][j] = min(dp[i][k] + dp[k+1][j] + arr[i-1]*arr[k]*arr[j]) ⏱️ O(n³) time, O(n²) space #DynamicProgramming #MCM #gfg160 #100DaysOfCode #geekstreak2025 @geeksforgeeks
![YojitKataria's tweet image. 🚀 Day 138: Matrix Chain Multiplication
Solved using DP + Optimal Parenthesization 💡
✔️ Recurrence: dp[i][j] = min(dp[i][k] + dp[k+1][j] + arr[i-1]*arr[k]*arr[j])
⏱️ O(n³) time, O(n²) space
#DynamicProgramming #MCM #gfg160 #100DaysOfCode #geekstreak2025
@geeksforgeeks](https://pbs.twimg.com/media/GypdFdvX0AMYtqc.jpg)
![YojitKataria's tweet image. 🚀 Day 138: Matrix Chain Multiplication
Solved using DP + Optimal Parenthesization 💡
✔️ Recurrence: dp[i][j] = min(dp[i][k] + dp[k+1][j] + arr[i-1]*arr[k]*arr[j])
⏱️ O(n³) time, O(n²) space
#DynamicProgramming #MCM #gfg160 #100DaysOfCode #geekstreak2025
@geeksforgeeks](https://pbs.twimg.com/media/Gypld7BX0AEVbpn.jpg)
12 August, 2025 ✅Solved: ✅Assign Cookies using two-pointer approach ✅Coin change I ✅Target Sum, through memoization, tabulation, and space optimization #100DaysOfCode #DynamicProgramming #LeetCode #java



💻 DSA Day 55 Today I learned Best Time to Buy & Sell Stock (DP on Stocks). Used Dynamic Programming (space optimized). Time Complexity: O(n) Space Complexity: O(1) 👉 Key Idea: Keep track of the minimum price & maximize profit. #100DaysOfCode #DSA #DynamicProgramming


📈 Day 133: LIS & LCS Double DP dose today! ✔️ Longest Increasing Subsequence ✔️ Longest Common Subsequence – classic 2D DP table approach #DynamicProgramming #LIS #LCS #gfg160 #100DaysOfCode #geekstreak2025 @geeksforgeeks



Day 63 of #100DaysOfCode 🚀 Solved Minimum Score Triangulation of Polygon (LeetCode 1039). #LeetCode #DynamicProgramming #ProblemSolving

Leetcode 1092. Shortest Common Supersequence Build LCS table to find overlaps 1️⃣ If chars match - extend sequence 2️⃣ If not - take max from left/top 3️⃣ Backtrack through DP table to build final supersequence #DynamicProgramming #LearnInPublic #LeetCode

139. Word Break - Leetcode solution in Golang. #dynamicprogramming #golang #dsa

I spent nearly 30 mins debugging why this memoized solution is timing out. Laughed at myself after realizing the mistake😂

🚀 Day 359 of Code 🚀 Solved: ✅ 3202. Find the Maximum Length of Valid Subsequence II #Day359 #DynamicProgramming #2DDP #LeetCode #CodingChallenge #DSA #Greedy #Subsequence #TechJourney #ProblemSolving

Leetcode 300. Longest Increasing Subsequence 1️⃣ Naive recursion: take/skip - exponential 2️⃣ Add "last chosen index" - valid subsequences 3️⃣ Memoize (ind,last+1) Brute -> State -> DP #LearnInPublic #100DaysOfCode #DynamicProgramming #LeetCode

🚀 Day 142: Edit Distance Classic DP on Strings problem 💡 ✔️ Allowed operations: Insert, Delete, Replace #DynamicProgramming #Strings #EditDistance #gfg160 #100DaysOfCode #geekstreak2025 @geeksforgeeks

Something went wrong.
Something went wrong.
United States Trends
- 1. #VSFashionShow 300K posts
- 2. #youtubedown 12.5K posts
- 3. #AEWDynamite 5,291 posts
- 4. quen 17.5K posts
- 5. Missy 9,039 posts
- 6. Angel Reese 23.8K posts
- 7. tzuyu 104K posts
- 8. jihyo 107K posts
- 9. madison 53.9K posts
- 10. Karol G 44.3K posts
- 11. #VictoriasSecretFashionShow 4,604 posts
- 12. #Survivor49 N/A
- 13. bella hadid 43.8K posts
- 14. Nancy 117K posts
- 15. Birdman 2,816 posts
- 16. UTEP 2,727 posts
- 17. Julio Rodriguez 1,123 posts
- 18. Candice 21.4K posts
- 19. nayeon 87.6K posts
- 20. Anok 24.3K posts