Remove Duplicates from Sorted Linked List

Day 49/60 #geekstreak60 Solved Segregate 0s and 1s today. A simple yet useful problem that teaches the power of the two-pointer approach — solving efficiently in O(n) time and O(1) space without extra memory. Small problems like these build strong problem-solving habits step by step. 💻 #geekstreak60 #npci #DSA #Python #ProblemSolving #CodingJourney

Day 106 Some problems feel simple when the pattern clicks. #Day106 🧩 17. Letter Combinations of a Phone Number How today went: • Used a digit → letters map • Built combinations using backtracking • Maintained a string path at each step • One recursive call per choice — no need for complex state handling What I realized: Once you understand the pattern: → choose a letter → move to next digit → build the path Backtracking becomes very natural. Simple problem, but great for building confidence. #LeetCode #DSA #Python #Backtracking #Recursion #LearningInPublic #Consistency

DSA Tip: Collision Handling What happens when two keys map to the same index? That’s called a collision. In hash tables, different keys can produce the same hash — but data must still be stored correctly. So we use collision handling techniques like: Chaining (store multiple values in one bucket) Open Addressing (find another empty slot) Insight: Efficiency isn’t just about speed, it’s about handling conflicts gracefully. Quick Challenge: If two keys hash to index 2, what should happen next? Drop your answer, I’ll review the best ones. FOLLOW FOR MORE DSA TIPS & INSIGHTS #DSA #HashTable #CollisionHandling #Python #CodingTips

Day 102 Backtracking patterns are starting to repeat. #Day102 🧩 90. Subsets II How today went: • Similar to the basic Subsets problem • Key difference: handling duplicates • Sorting the array is important • While iterating, skip duplicates to avoid repeating subsets What clicked: Backtracking becomes easier when you: • Recognize the base pattern • Add constraints like duplicate handling Same structure, new rule. That’s how patterns build. #LeetCode #DSA #Python #Backtracking #Recursion #LearningInPublic #Consistency

Day 117 Same pattern, one important tweak. #Day117 🧩 90. Subsets II How today went: • Same base as Subsets • First step: sort the array • While iterating, skip duplicates to avoid repeating subsets • Use the same pattern: append → recurse → pop What I learned: It’s not a new problem — it’s the same pattern with a duplicate filter. Small condition. Big impact. Backtracking is starting to feel predictable. #LeetCode #DSA #Python #Backtracking #Recursion #LearningInPublic #Consistency

🚀 Day 5 — DSA with Python Solved the classic “Product of Array Except Self” problem today. This one introduced me to an important concept: 👉 Precomputation (Prefix & Suffix Pattern) Instead of recalculating products again and again, I learned how to: • Store prefix products (left side) • Store suffix products (right side) • Combine them to get the result efficiently 💡 Key Learning: Optimizing brute-force solutions using precomputation can significantly reduce time complexity. ⚡ What challenged me: Understanding how to manage two passes (left → right and right → left) without using extra space initially felt confusing — but breaking it step by step helped. 📈 Growth Insight: DSA is less about memorizing solutions and more about recognizing patterns like this one. On to Day 6 🔥 #DSA #Python #CodingJourney #ProblemSolving #100DaysOfCode

🚀 Day 10/30 – Python Challenge Learning about tuples in Python today! 🐍 🔹 Key Concepts Covered: * Creating tuples * Accessing elements using index * Iterating through tuple elements using loops * Understanding immutability (tuples cannot be changed) 💻 Mini Task: Created a tuple of numbers, accessed the first element, and used a loop to display all the values. 🎯 Learning Outcome: Understood how tuples are used to store fixed collections of data and how they differ from lists. They are especially useful when data should not be modified. Building a strong foundation in data structures step by step 💪 #Python #CodingChallenge #LearningJourney #DataStructures #StudentDeveloper #Day10

Day 119 Same problem family, new constraint — but now it feels easier. #Day119 🧩 40. Combination Sum II How today went: • Very similar to Combination Sum • First step: sort the array • Move to i + 1 (each element used once) • Skip duplicates to avoid repeating combinations Key idea: 👉 No reuse of same element 👉 Handle duplicates carefully What I realized: Once you understand the base pattern, variants like this become much easier. Backtracking is starting to feel natural now. #LeetCode #DSA #Python #Backtracking #Recursion #LearningInPublic #Consistency

Day 110 Same pattern, new constraint. #Day110 🧩 90. Subsets II How today went: • Very similar to the basic Subsets problem • First step: sort the array • While iterating, skip duplicate elements to avoid repeating subsets • Use the same backtracking pattern: append → recurse → pop What I learned: The core pattern stays the same — only the duplicate handling logic changes. This small condition makes a big difference. Backtracking is becoming more predictable now. #LeetCode #DSA #Python #Backtracking #Recursion #LearningInPublic #Consistency

🚀 Solved today’s GeeksforGeeks Problem of the Day: Segregate 0s and 1s using Python 🐍 Problem: Given a binary array, rearrange it in-place such that all 0s come before 1s. Approach: Used the efficient Two Pointer Technique. ✔ Left pointer → finds misplaced 1 ✔ Right pointer → finds misplaced 0 ✔ Swap and move pointers inward 💡 Key Insight: No need for extra space or sorting — we can solve this in O(n) time and O(1) space using pointers. 💡 Concepts Used: Two Pointers | Array Manipulation | In-place Algorithm Sometimes, the simplest problems reinforce the most important techniques used in complex scenarios 🔁 #geekstreak60 #geeksforgeeks #dsa #python #coding #problemSolving #arrays #twopointers