Pwrteams’ Post

LeetCode Win Today 🚀 Solved “Apply Operations to an Array” with a simple two-pass approach. ⚡ Runtime: 0 ms (Beats 100%) Approach: 🔹 Pass 1: Traverse the array If nums[j] == nums[j-1] → Double the left element → Set the right element to 0 🔹 Pass 2: Move all zeros to the end using a two-pointer technique. 💡 Key Insight: Instead of solving everything in one complex loop, split the problem into two clean steps. 📊 Complexity: • Time → O(n) • Space → O(1) (in-place) Consistent practice. Clear thinking. Better code every day. 🧠⚡ #leetcode #dsa #algorithms #datastructures #coding #programming #python #softwareengineering #computerscience #tech #codinglife #problem-solving #100daysofcode #developers #codingjourney #techcommunity 🚀

𝗧𝗪𝗢 𝗠𝗢𝗡𝗧𝗛𝗦 𝗜𝗡𝗧𝗢 𝗡𝗘𝗘𝗧𝗖𝗢𝗗𝗘 𝟭𝟱𝟬 Lately, I’ve been focusing on patterns over problem count. Instead of checking boxes, I am trying to understand why an approach works. Arrays, hashmaps, sliding window, two pointers, the same ideas show up in different but related problems. I’m still using NeetCode as my guide and solution reference, working through problems one at a time. I realized every day is not about finishing a new problem. Sometimes, I go back to one I already tried because I didn’t fully understand it (or remember the pattern) the first time. Here’s what practice actually looks like for me: - Some days I tackle a new problem - Some days I redo one I half-understood - I always go back to the earlier problems - I split time between DSA (Python) and SQL - I write/draw out my approach first, then think through it Most of my code right now could be written by AI. But actually solving problems myself (figuring out the logic, tracing cases, thinking through mistakes) keeps my brain active and my critical thinking sharp. It’s basic, but it’s fresh and rewarding. LeetCode: https://lnkd.in/gG7ZuCRM #LearningInPublic #LeetCode #NeetCode #DSA #Python #SQL #ProblemSolving #DataEngineering #DataScience #DataAnalytics #OpenToWork

The future programming language might be... English. Jensen Huang believes Al is changing how humans interact with computers. Instead of writing syntax-heavy code in C++ or Python, people will describe what they want in natural language and Al will generate the software. With generative tools already building apps, automating workflows, and fixing errors through conversation, programming is shifting from writing instructions to expressing intent. Debugging could become as simple as telling the system what went wrong and asking it to correct itself. The barrier to building software may soon depend less on coding knowledge and more on how clearly you can communicate your ideas. #AI #MachineLearning #NVIDIA #JensenHuang #AIInnovation #GenerativeAI #DeepLearning #DataScience #TechLeadership

🚀 Day 6 of My Daily Coding Challenge Solved LeetCode 1545 – Find Kth Bit in Nth Binary String today. At first, it looks like a string construction problem. But building the full string would be inefficient since its length grows exponentially (2ⁿ - 1). 💡 Key Insight: The string follows a recursive pattern: Left half → S(n-1) Middle → always '1' Right half → reverse + invert of S(n- 1) Instead of constructing the string, I used recursion and symmetry: If k is in the left half, then solve for n-1 If k is the middle, then the answer is '1.' If k is in the right half, mirror the position and invert the result This approach reduces the problem to O(n) time instead of exponential. What I learned today: Don’t simulate when math/pattern recognition can solve it. Recursive structure often hides optimization opportunities. Understanding the pattern is more powerful than brute force. Day 6 done. Staying consistent 🔥 On to Day 7. #LeetCode #DailyChallenge #Python #Recursion #ProblemSolving #CodingJourney #Consistency

✅ Day 51 of 100 Days LeetCode Challenge Problem: 🔹 #973 – K Closest Points to Origin 🔗 https://lnkd.in/gzp_xraa Learning Journey: 🔹 Today’s problem focused on finding the k points closest to the origin in a 2D plane. 🔹 I calculated the squared Euclidean distance for each point to avoid unnecessary square root operations. 🔹 Using a min-heap, I efficiently retrieved the smallest distances. 🔹 A hashmap helped group points with the same distance, ensuring correct retrieval of coordinates. Concepts Used: 🔹 Heap / Priority Queue 🔹 Euclidean Distance 🔹 Hash Map 🔹 Greedy Selection Key Insight: 🔹 Squared distance is sufficient for comparison and avoids extra computation. 🔹 Heaps are ideal for efficiently extracting the smallest (or largest) k elements. 🔹 Choosing the right data structure significantly simplifies implementation. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

🎙️ New episode of Breaktime Tech Talks is out! In Ep71, I dig into lessons learned building a GraphRAG app with Neo4j's Python package — including why letting the LLM decide your entire data model is a mistake and how providing entity/relationship patterns as boundaries makes all the difference. I also break down standout takeaways from Lize Raes' Devoxx Belgium talk on taking Langchain4j apps to production: wrapping RAG as an agent tool, programmatic tool filtering, sub-agent orchestration, and skipping unnecessary LLM hops to save tokens and latency. Give it a listen if you're working with knowledge graphs, RAG, or agentic architectures. 🎧 Listen: https://pod.fo/e/3b557d #btt #GraphRAG #Neo4j #Langchain4j #Java #Python #AI #LLM #AgenticAI #DevLife

Day 2: 90-Day Coding Challenge 🚀 Continuing the 90-day journey by exploring grid traversal and recursion-based problem solving. Today’s problem focused on the Number of Islands challenge, which involves identifying groups of connected land cells in a grid. Each island is formed when land cells are connected horizontally, vertically, or diagonally across all 8 directions. Today’s learning highlights: ✅ Understanding how connected components can be identified in grid problems ✅ Applying Depth First Search (DFS) to traverse and mark visited land cells ✅ Handling boundary conditions while exploring all 8 directions in the grid This problem strengthened my understanding of how recursive traversal techniques can efficiently solve matrix-based connectivity problems. Day 2 done. On to Day 3. 💻🔥 #90DayCodingChallenge #CodingJourney #DSA #ProblemSolving #Python #LearningJourney #Consistency #Growth

🚀 LeetCode Win: Rearranging Array Elements by Sign Solved the problem “Rearrange Array Elements by Sign” today and wanted to share the thought process behind my solution. 🔹 Problem Overview Given an array with equal numbers of positive and negative integers, the task is to rearrange it so the elements alternate between positive and negative, starting with a positive number. 💡 My Approach Instead of handling complex index manipulation directly, I simplified the problem into two clear steps: 1️⃣ Separate the elements I first traversed the array once and grouped the numbers into two lists: one containing all the positive numbers one containing all the negative numbers This step also ensures that the relative order of elements remains unchanged. 2️⃣ Rebuild the array alternately Since the count of positive and negative numbers is equal, I then constructed the final array by alternately placing: one positive number one negative number This results in a sequence like: positive → negative → positive → negative ⚙ Complexity • Time Complexity: O(n) • Space Complexity: O(n) 📌 This problem reinforced an important lesson: Sometimes the cleanest solution comes from breaking the problem into smaller logical steps rather than forcing a complex one-pass trick. Consistently practicing DSA and problem-solving one challenge at a time. 💻✨ #LeetCode #DSA #Python #ProblemSolving #CodingJourney #SoftwareEngineering #WomenInTech #LearningInPublic

💻 Breaking down logic, one problem at a time. 🚀 #LearnDSAWithAyman | Problem 34 – Kth Distinct String in an Array Platform: LeetCode 2053 🧠 Concepts Used: Frequency Counting + Order Preservation ✅ Approach: Count the frequency of each string in the array. Traverse the array again in original order. Return the k-th string whose frequency is exactly 1. If none found, return an empty string. ⚡ Result: Runtime: 0 ms (beats 100.00%) 💡 Pro Tip: When a problem requires both uniqueness and original order, always separate counting and traversal—it keeps the logic clean and reliable. 💬 Have a DSA question or LeetCode problem you want me to solve next? Drop it below 👇 #DSA #Python #ProblemSolving #LeetCode #LearningInPublic #CodingJourney #Tech #LearnDSAWithAyman Akarsh Vyas Tanishq Vyas Dhanesh Parwati Malviya Sheryians Coding School Sheryians AI School

🦀 It’s time for me to explore this more in depth… After a few months exploring Rust - and slowly appreciating what it brings (even if I don’t really like the idea of "loving" a programming language 😅) - it’s time for the next step: ROS-Z I’ve already experimented with rclrs, the Rust bindings for ROS 2. Architecturally, it looks like this: Rust → C++ → Rust You get some benefits of Rust, yes. But under the hood, you’re still crossing language boundaries through the traditional ROS 2 stack. That’s exactly why the team at ZettaScale Technology (the people behind Zenoh) are building ROS-Z. With ROS-Z, the idea is different: 👉 stay fully in Rust, end-to-end. And the good news? It remains interoperable with traditional ROS 2 nodes. It’s still experimental - so this is clearly exploration mode for me. But I’m curious enough to give it a serious try and share feedback soon. Have you experimented with ROS-Z yet? 👇 #rust #ros2