Manas Mishra’s Post

🚀 Enhancing My DSA Skills with Rohit Negi's YouTube Course! 💻📈 I'm currently diving deep into Data Structures and Algorithms, guided by Rohit Negi Bhaiya's comprehensive DSA course on YouTube. Here are some key highlights from my recent study sessions: 🔍 Key Problems and Concepts Explored: 1. Kth Missing Positive Number 📊 Problem Statement: Given an array of sorted positive integers, find the Kth missing positive number in the sequence. Approach: Utilized binary search to efficiently narrow down the missing count. Time Complexity: O(log n), achieving a significant improvement over linear search. 2. Book Allocation Problem 📚 Scenario: Divide n books among m students such that the maximum number of pages assigned to a student is minimized. Optimal Solution: Implemented binary search to allocate books while balancing the load. Core Idea: Minimize the maximum number of pages a student reads, aiming for an O(n log n) complexity. 3. Painter Partition Problem 🎨 Problem: Given n boards and k painters, minimize the time to paint all boards under the condition that a painter can only paint consecutive boards. Solution: Applied a binary search strategy with the concept of feasible partitions, optimizing the time allocation among painters. 4. Time and Space Complexity Analysis ⏳ Essentials Covered: Big O Notation: Understanding the worst-case scenario and its impact on algorithm performance. Optimizations: Evaluated different data structures and techniques for reducing time and space overhead. #DSA #CodingJourney #ProblemSolving #Algorithms #RohitNegiDSA #ContinuousLearning #LinkedInLearning

🌟 Hello everyone! Day 21/100 of my DSA Journey! Today's challenges delved into the world of sequences and system design, offering two intriguing problems to solve. 🧩💡 1) Minimum Appends for Subsequence (Medium): I tackled the task of finding the minimum number of characters needed to be appended to a string s so that another string t becomes a subsequence of s. This problem required careful analysis of string manipulation and algorithmic thinking to efficiently determine the solution. • Dive into the problem here: https://lnkd.in/gyqGje4a 🔍 2) TinyURL System Design (Medium): In this companion problem to the System Design challenge, I designed a class to encode and decode URLs, similar to the functionality of TinyURL. This problem allowed me to explore system design concepts and implement an efficient encode/decode algorithm for generating tiny URLs. • Explore the problem here: https://lnkd.in/g-5hd2Tt 📊 These challenges not only tested my technical skills but also deepened my understanding of system design principles and string manipulation techniques. How's your progress with DSA challenges? Share your insights or connect with me to discuss further! Let's keep learning and growing together. 💪✨ #100DaysOfDSA #DataStructures #Algorithms #CodingChallenge #ProblemSolving #ProgrammingJourney #TechSkills #CodeNewbie #DailyCoding #AlgorithmicThinking #DSAPractice #CodingCommunity #TechDevelopment #SystemDesign

I have compiled a short "Master Thesis Frequently Asked Questions and Answers for our International Students" at the Otto-von-Guericke-Universität Magdeburg and published this as a blog post: https://lnkd.in/dmKWxj4r Answers are discussed for the following question: 1. When choosing a topic, do students usually browse the departmental websites to find a suitable topic and then contact the supervisors? If so, what is the next step after this initial contact? 2. What are the general expectations of the supervisor in terms of support to ensure timely completion of the thesis? Is it possible to arrange regular (e.g. weekly) catch-up meetings or phone calls with the supervisor? 3. If I am interested in a particular topic but do not have certain skills required for it (e.g. Python), would this prevent me from completing my thesis? Is there room for skills development during the thesis? 4. If I were to propose my own thesis topic to a particular professor or department, is there a set format for submitting a thesis proposal? 5. What does it mean to register a thesis? Are students allowed to work on the topic before registering it? I have heard that the thesis should not be registered until substantial progress has been made, possibly halfway through the work. Is this correct? 6. When does the thesis defence take place? Is there any flexibility in arranging the defence date once the thesis has been registered? Can a student freely choose the date of the defence? 7. On average, how long do students typically take to complete a master’s thesis? In your opinion, would it be feasible to start looking for a topic in October and aim to complete the thesis by the end of April next year?

Hello connections👋👋 #30 DAYS DSA CHALLENGE: #DAY 25 Title: Mastering Algorithmic Challenges: Solving Power of Three Dilemma Intro: Are you ready to delve into the world of algorithmic problem-solving? Join me as we dissect a common coding challenge and explore the intricacies of efficient solution strategies. Today, let's tackle the classic "Power of Three" problem. Problem Statement: The task at hand is to determine whether a given integer is a power of three. Sounds simple, right? Well, let's dive into the code and unravel the solution step by step. Solution Breakdown: Handling Edge Cases: The function begins by checking if the input number n is less than or equal to zero. If it is, the function immediately returns False, as no non-positive number can be a power of three. Iterative Approach: The heart of the solution lies in the while loop. While n is divisible by 3, it keeps dividing n by 3. This process effectively checks if n can be reduced to 1 by successive divisions by 3. Final Verification: After the loop exits, the function verifies if n equals 1. If it does, True is returned, indicating that the original input is indeed a power of three. Complexity Analysis: The time complexity of this solution is logarithmic, O(logn), where 'n' is the input number. This is because we are continually dividing 'n' by 3 until we reach 1 or a non-divisible number. #PythonProgrammig #ProblemSolving #LinkedInLearning

🚀 DSA Challenge: Days 127-132 🚀 Over the past six days, I've been tackling various graph problems and consistently maintaining my LeetCode streak. Here's a snapshot of my journey: 🌟 Graph Problems: 1. Distance of Nearest Cell Having One - Implemented BFS to determine the shortest path to the nearest cell containing 1. 2. Surrounded Regions (Replace O's with X's) - Used DFS to transform all surrounded regions of 'O' into 'X'. 3. Number of Enclaves - Identified enclaves, or land cells not connected to the boundary, using DFS. 4. Number of Distinct Islands - Counted unique island shapes by employing DFS. 5. Detecting if a Graph is Bipartite - Verified if a graph can be colored with two colors using BFS/DFS. 🏆 LeetCode Streak: Maintained my streak by solving the following problems each day: - Day 127: Number of Ways to Reach the Kth Stair - Day 128: Sum of All Subset XOR Totals - Day 129: Number of Beautiful Subsets - Day 130: Maximum Score Words Formed by Letters - Day 131:Word Break II - Day 132: Student Attendance Record II 🔥 Key Takeaways: - Graph algorithms are essential for solving complex connectivity and traversal problems. - Consistency is key to mastering problem-solving skills—daily practice makes a huge difference. - Breaking down problems into smaller, manageable parts is crucial for efficient solutions. 🙏 Shoutout: A huge shoutout to raj vikramaditya for his amazing DSA sheet and insightful lectures on YouTube. Your resources have been incredibly helpful on this journey. Thank you for making complex concepts so accessible! 📈 What's Next? I'm excited to continue this journey with more challenging problems and broaden my knowledge in Data Structures and Algorithms. Stay tuned for more updates! 💬 Have you encountered any interesting problems lately? Share your experiences in the comments! #DSA #GraphAlgorithms #LeetCode #CodingChallenge #ProblemSolving #ConsistencyIsKey #LearningJourney #Striver #ThankYou

"Branch-Train-MiX: Mixing Expert LLMs into a Mixture-of-Experts LLM" accepted to COLM!!! 🎉 🎉 🎉 Kudos to the team for the great work and looking forward to exploring all the cool possible extensions of the work! Abstract: We investigate efficient methods for training Large Language Models (LLMs) to possess capabilities in multiple specialized domains, such as coding, math reasoning and world knowledge. Our method, named Branch-Train-MiX (BTX), starts from a seed model, which is branched to train experts in embarrassingly parallel fashion with high throughput and reduced communication cost. After individual experts are asynchronously trained, BTX brings together their feedforward parameters as experts in Mixture-of-Expert (MoE) layers and averages the remaining parameters, followed by an MoE-finetuning stage to learn token-level routing. BTX generalizes two special cases, the Branch-Train-Merge method, which does not have the MoE finetuning stage to learn routing, and sparse upcycling, which omits the stage of training experts asynchronously. Compared to alternative approaches, BTX achieves the best accuracy-efficiency tradeoff. Link: https://lnkd.in/gyJ-ScZj

My first project using python in analyzing the orders from a food aggregator company. Lot to improve but proud of baby steps. Skills & Tools Covered: EDA, Data Visualisation, Statistics.

Day 38 of Learning DSA! LeetCode - problem 1920: Build Array from Permutation! Problem: Given an array nums, create a new array result such that result[i] is equal to nums[nums[i]]. In other words, we had to create a new array by using the values in the original array as indices to pick elements from the original array itself. Approach: While the problem statement sounded a bit convoluted, the solution was surprisingly straightforward. 1- I used a simple loop to iterate through the original array nums, and for each index i, I first retrieved the value nums[i] and used it as an index to access the corresponding element in nums. This element was then stored in the result array at index i.

My Roadmap to learning GIS Analysis 🛣 🗺 BEGINNING SKILLS: Python Programming ~ Learned Python Syntax, variables, data types, and modules/libraries for geoproecessing 🐍 .  🔗https://lnkd.in/deePxiJB || https://lnkd.in/dUAd48UN  || https://lnkd.in/d2Yqagh8   Geospatial data ~ Retrieved vector and raster data from web services and with python scripts 🌏 .   🔗https://lnkd.in/dWNwwDAe  ||  https://lnkd.in/dkUGhDfb || https://lnkd.in/dc2dw5Hp DATA ANALYSIS AND VISUALIZATION: (Python Packages and Softwares)  ~ Pandas / Geopandas  ~ Shapely Geometry  ~ MapClassify  ~ Matplotlib  ~ Google Earth Engine  ~ Geemap ~ Folium  ~QGIS et c. TOOLS AND TECHNOLOGIES: Visual Studio Code (VS Code): Code editor with support for development operations like debugging, task running, and version control 👩💻 .  🔗https://lnkd.in/dRCJfdrZ Jupyter Notebooks: Creates interactive codes, equations, visualizations, media and other computational outputs 🔗https://jupyter.org/ Git and Github : Manage multiple versions of source code edits that are then transferred to files in a Git repository, GitHub. 🔗https://www.git-scm.com/  || https://github.com/ PRACTICE AND PROJECTS: Scripting: Developed small projects while adhering to Python syntax. Additionally, wrote and read geographic data using Python packages, analyzing the information and creating visualizations. Softwares: Utilized the QGIS software to read geographic datasets, analyse the data and visualized it as maps, graphs and animations 📈 .  🔗https://lnkd.in/dHfCW8hK #GIS #SpatialAnalysis #DataVisualization #UrbanPlanning #EnvironmentalImpact #TrafficMonitoring #DisasterResponse #Agriculture #Python #ArcGIS #QGIS #Geospatial

--- 🌟 **Bringing Advanced Mathematics to Life with Code!** 🌟 After months of diving deep into algorithms and working on my BCA 6th-semester project, I’m excited to share a preview of what I've been building! 🚀 🔍 Imagine solving complex mathematical problems with the click of a button. That’s what my project, **Advanced Mathematical Solution System**, is all about. Whether it’s the Newton-Raphson method or the Runge-Kutta approach, I’ve integrated cutting-edge algorithms into an easy-to-use **Python GUI**. The goal? To make advanced problem-solving more accessible to everyone. 💻 📈 From root-finding to numerical integration, my system offers solutions across a wide range of mathematical challenges, with a user-friendly interface that empowers users to explore methods like Bisection, Simpson’s Rule, and Euler’s Method. This journey has taught me the power of combining theory with technology—and how it can transform the way we solve problems. 💡 Curious to know more or want a demo? Let’s connect and chat! connect me https://lnkd.in/gAnrBrMT #MathematicsInTech #PythonProgramming #NumericalMethods #BCAProjects #TechForGood ---