"Day 64: Counting Distinct Subsequences with DP"

Day 44 of #100DaysOfCode, solving "Longest Common Subsequence (LCS)." This problem requires finding the longest sequence common to two strings, even if characters are separated. My solution uses Dynamic Programming (DP), which breaks the problem into smaller, overlapping subproblems. DP Table: I built a table (optimized to use only the previous row) to store the length of the LCS found so far. The Rule: If characters match, the LCS length increases by 1 (coming from the diagonal cell). If they don't match, the length is the maximum of the two adjacent cells. This systematic approach guarantees the optimal result, solving the problem in O(m * n) time complexity. #Python #DSA #Algorithms #DynamicProgramming #LCS #100DaysOfCode #ProblemSolving

Day 7 of #100DaysOfLeetCode Problem: 5. Longest Palindromic Substring Category: Strings / Two Pointers / Dynamic Programming Today’s challenge was about finding the longest palindromic substring within a given string. This problem helped me improve my understanding of string traversal and palindrome validation using substring slicing. 🧠 Key Learnings: Iterated through all possible substrings to check for palindromes. Compared each substring with its reverse to find the longest one. Reinforced the concept of two-pointer expansion and string symmetry. Understood how optimizing brute-force logic can significantly reduce time complexity in future attempts. 🎯 Takeaway: Palindrome problems are all about symmetry — once you recognize that, expanding around centers or slicing becomes much more intuitive. #LeetCode #100DaysOfCode #ProblemSolving #CodingJourney #Strings #TwoPointers #Python #AIEngineer #Consistency

Introducing our REV Estimator 🤝 If you didn’t know yet, IPSDK Explorer includes a free, Python-ready plugin for Representative Elementary Volume (REV) analysis ! ✨ No need to be an image analysis expert, REV Estimator helps you determine your dataset’s REV with just a few clicks 🧠 It’s fast, robust and fully customizable : ✅Define the optimal dataset size to save computing time and workstation requirements, without impacting the final result ✅Adjust parameters based on dataset size and variability ✅Access and modify the Python code to make it your own Simplify your workflow and gain accurate, noise-free REV measurements : for free 🤗 #IPSDKExplorer #OpenSource #Python #REV #ImageAnalysis #MaterialsScience #Innovation #DataAnalysis 

💡 Day 64 of #LeetCode365 Problem: 338. Counting Bits Category: Bit Manipulation | Dynamic Programming Today’s problem was all about counting 1s in binary numbers — basically, checking how “on” each number is 💡😅 💻 Approach: 👉 Use a DP array ans to store counts of 1s for each number. 👉 For each number: If it’s even ➡️ same count as i/2 If it’s odd ➡️ one more than (i−1) ans = [0, 1, 1] for i in range(3, n + 1): if i % 2 == 0: ans.append(ans[i // 2]) else: ans.append(ans[i - 1] + 1) return ans[:n + 1] ⚙️ Complexity: ⏱ O(n) | 💾 O(n) 💡 Lesson: Bits are like people — some are off, some are on, but together, they make the system work 😎💻 #LeetCode #Python #DynamicProgramming #BitManipulation #CodingHumor #100DaysOfCode #FunnyCode

Day 62 Of #100DaysOfCode Problem #3354: Make Array Elements Equal to Zero Successfully solved today’s problem with an optimized solution achieving 93.09% runtime efficiency and 95.74% memory optimization! 🚀 🧩 Problem Insight: Given an integer array, the task is to determine the number of valid selections of a starting index and direction that reduce all array elements to zero by following specific movement and decrement rules. ⚙️ Approach: Used prefix/suffix summation logic to track balance between left and right movements. Calculated total sum and suffix sums efficiently to identify valid starting points. Achieved O(n) time complexity using cumulative tracking. 🧠 Language: Python ✅ Result: Accepted | Beats 93.09% in Runtime, 95.74% in Memory #LeetCode #Python #ProblemSolving #CodingChallenge #Mythyly #DailyPractice #DSA #ProgrammingJourney #WomenInTech

LeetCode 90-Day Challenge – Day 73 Problem: Interleaving String Difficulty: Medium Problem: We’re given three strings s1, s2, and s3. We need to determine if s3 can be formed by interleaving s1 and s2. An interleaving means taking characters from both strings in order but not necessarily alternating evenly as long as the original order of each string is preserved. Solution approach: This problem can be solved using Dynamic Programming. We create a 2D table dp[i][j] where each cell represents whether the first i characters of s1 and first j characters of s2 can form the first i + j characters of s3. We fill this table by checking if the current character from s1 or s2 matches the corresponding character in s3. If either condition holds true, we mark that state as valid. The answer will be the value at dp[len(s1)][len(s2)]. #LeetCode #90DaysOfCode #Python #DynamicProgramming #LeetCodeChallenge #CodingJourney #ProblemSolving

From equations on paper to code: Define state space models instantly with python and c4dynamics 🔥 c4dynamics brings the legacy of state space modeling into the Python era: The state vector isn’t just math. It’s programmable: s = state(x=180, v=0) print(s.X) # [180, 0] One framework. One philosophy. The same pursuit that started centuries ago: understanding how systems move, react, and adapt. State space programming is the future of dynamical systems. What’s stopping you from turning your models into code?

c4dynamics brings the legacy of state space modeling into the Python era: The state vector isn’t just math. It’s programmable: s = state(x=180, v=0) print(s.X) # [180, 0] One framework. One philosophy.

Built an automated college timetable generator using Python & backtracking algorithms. The system handles multiple constraints (teacher availability, room conflicts, lab scheduling) and generates conflict-free schedules for entire institutions. Features Tkinter GUI, SQLite database, and exports to Excel/PDF. Solving the classic scheduling problem with practical automation. #Python #CSP #SoftwareDevelopment

Excited to share my latest project — a GUI-based Calculator built using Python’s Tkinter library! 🎉 It performs basic arithmetic operations like addition, subtraction, multiplication, and division — all through a clean, user-friendly interface. This project helped me strengthen my understanding of GUI development in Python and event-driven programming. 🔗 Check it out on GitHub: https://lnkd.in/etAfPTGD #Python #Tkinter #GUI #Coding #PythonProjects #SoftwareDevelopment #LearningByDoing