Count Pairs with Sum Target using Two-Pointer Technique

LeetCode | Count Good Numbers 🔢 🔹 Concept: Combinatorics + Modular Exponentiation 🔹 Idea: Even positions → 5 choices, Odd → 4 choices 🔹 Time Complexity: O(log n) Use math + fast power to handle large inputs efficiently 💡 #LeetCode #DSA #Math #ModularArithmetic #Python #CodingJourney

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

🔁 Exploring Sorting Algorithms in Python Today I practiced two fundamental sorting techniques: ✅ Bubble Sort ✅ Selection Sort 💡 Key Learnings: * Bubble Sort repeatedly swaps adjacent elements to push larger elements to the end * Selection Sort selects the minimum element and places it in the correct position * Understanding time complexity becomes clearer when you count operations manually #Python #DataStructures #Algorithms #CodingJourney #100DaysOfCode #LearningInPublic

Day 103/200 – LeetCode Challenge. Today’s problem: Subsets II Given an integer array that may contain duplicates, return all possible subsets without duplicate subsets. Handling duplicates is the tricky part. Sort input → groups duplicates together. Use backtracking to explore all subsets. Optimized and clean solution using recursion. How to handle duplicates in subset problems. Importance of sorting in backtracking. Writing efficient recursive solutions. #LeetCode #Python #CodingJourney #Backtracking #200DaysOfCode

🚀 Day 11 of #500DaysOfCoding Today’s problem: Maximum Average Subarray I I used the sliding window technique to solve this problem and reduced the time complexity to O(n). 💡 Key Takeaways: - Precompute the sum of the first window - Slide the window by adding the next element and removing the previous one - Track the maximum sum → compute the maximum average. On to Day 12 🔥 #CodingJourney #DataStructures #Algorithms #Python #ProblemSolving

What if you could improve LLM responses without training bigger models? That’s the idea behind Inferscale 0.1.1. A lightweight Python package that applies inference-time scaling techniques to produce higher-quality outputs—perfect for developers working within tight compute budgets. It’s simple, effective, and ready to use. Explore the repo and README: https://lnkd.in/giq8KJ5g Let me know what you think! #ArtificialIntelligence #LLM #Python #OpenSourceProject #AIInnovation #DeepLearning

Day 109 Backtracking patterns are repeating again — and that’s a good sign. #Day109 🧩 78. Subsets How today went: • Used recursion to explore all elements • At each step, decide to include or skip the current element • Append current subset → explore → then pop to backtrack • Move to the next index and repeat What I’m noticing: Subsets is one of the cleanest backtracking patterns: → choose → explore → undo Another revision day, but clarity is improving. Consistency continues. #LeetCode #DSA #Python #Backtracking #Recursion #LearningInPublic #Consistency

🐍 Day 89 — Features and Labels Day 89 of #python365ai 📌 Features (X) → input variables Labels (y) → output Example: X = [size, rooms] y = price 📌 Why this matters: Clear distinction is essential for building ML models. 📘 Practice task: Identify features and labels in a dataset. #python365ai #Features #MachineLearning #Python

📘 Currently diving deep into Algorithms using Python and it's been an eye-opening journey! From basics like arrays and searching to powerful concepts like sorting algorithms, linked lists, and recursion—this resource breaks everything down with simple explanations and visuals, making complex topics easier to grasp. Consistency + practice = real understanding. #Python #Algorithms #DataStructures #LearningJourney #Coding

💡 Solved Group Anagrams today! 🧠 Key idea: Instead of comparing strings, I used a frequency array (size 26) to create a unique key for each word. ⚠️ Catch in constraints: All characters are lowercase English letters, which allows us to use a fixed-size array of 26 for efficient hashing. 🚀 Result: Achieved O(n · k) time complexity. Great example of converting a comparison problem into a hashing problem! #LeetCode #DSA #Algorithms #Python #CodingInterview