Understanding Merge Sort Algorithm Internally

Some problems don’t have one answer — they require exploring all possibilities. Day 19/100 — Data Structures & Algorithms Journey Today’s Problem: Different Ways to Add Parentheses This problem introduced me to a powerful concept — Divide and Conquer using recursion. Approach: Instead of evaluating the expression directly, I split the expression at every operator. For each split, I recursively solved the left and right parts and then combined the results. This allowed me to generate all possible outcomes based on different ways of placing parentheses. Key Takeaways: - Recursion helps explore multiple possibilities - Divide and Conquer simplifies complex expressions - Breaking problems into smaller parts makes them easier to solve This problem improved my understanding of recursive thinking and expression evaluation. #DSA #LeetCode #Recursion #DivideAndConquer #ProblemSolving #SoftwareEngineering #CodingJourney #100DaysOfCode #TechLearning #DeveloperJourney #Programming #Python #InterviewPreparation #CodingSkills #ComputerScience #JobReady #FutureEngineer #TechCareers #SoftwareDeveloper #LearnInPublic #OpenToWork

Learning DSA is not just about solving problems, it’s about building a strong foundation of core concepts. Day 42/100 — Data Structures & Algorithms Journey Today I focused on going deeper into core DSA topics instead of just practicing random problems. I’m starting to understand that strong fundamentals are what make complex problems easier to solve. Today’s Focus: Strengthening basics of arrays and strings Deep diving into Sliding Window and Two Pointer techniques Understanding time and space complexity clearly Learning how different patterns connect with each other Why this matters? Because advanced problems are just combinations of strong basics. Key Takeaways: Strong fundamentals make problem-solving easier Patterns are built on top of basic concepts Understanding complexity improves decision making Deep learning leads to long-term retention This phase is all about building a solid base before moving into more advanced topics. Not rushing… just building strong foundations #Day42 #DSA #LeetCode #ProblemSolving #SoftwareEngineering #CodingJourney #100DaysOfCode #TechLearning #DeveloperJourney #Programming #Python #InterviewPreparation #CodingSkills #ComputerScience #FutureEngineer #TechCareers #SoftwareDeveloper #LearnInPublic #Consistency

Sometimes, solving a problem efficiently is about choosing the right direction. Day 15/100 — Data Structures & Algorithms Journey Today’s Problem: Merge Sorted Array Approach: The goal was to merge two sorted arrays into one, without using extra space. Instead of merging from the beginning, I used a two-pointer approach starting from the end of both arrays. By comparing elements from the back and placing the larger one at the last available position, I avoided overwriting existing values and achieved an efficient in-place solution. Key Takeaways: Thinking in reverse can simplify in-place problems Two-pointer technique is powerful for sorted data Avoiding extra space improves efficiency Learning to think differently with each problem. #DSA #LeetCode #ProblemSolving #SoftwareEngineering #CodingJourney #100DaysOfCode #TechLearning #DeveloperJourney #Programming #Python #InterviewPreparation #CodingSkills #ComputerScience #JobReady #FutureEngineer #TechCareers #SoftwareDeveloper #LearnInPublic #OpenToWork

📊 Linear Regression from Scratch — OLS + SGD I built Linear Regression from scratch in Python — no sklearn, only math and numpy. This wasn’t just coding. I went step by step: • Derived OLS using matrix form • Implemented SGD from gradients • Verified results against sklearn Final result: R² ≈ 0.994 (matched sklearn closely) This project helped me understand what actually happens behind .fit() — not just use it blindly. 📖 Article: https://lnkd.in/grC8jMk2 💻 Code + Notes: https://lnkd.in/gPb6BTNv If media quality drops on LinkedIn, everything is available clearly in the repo. I’m currently building ML algorithms from scratch to strengthen fundamentals. Next: Logistic Regression. #MachineLearning #Python #DataScience #LinearRegression #MLFromScratch #OpenToWork

Sometimes, organizing the data first makes the solution much simpler. Day 18/100 — Data Structures & Algorithms Journey Today’s Problem: Merge Intervals Approach: I started by sorting the intervals based on their starting values. Then, I iterated through the list and compared each interval with the last merged interval. If there was an overlap, I merged them by updating the end value. Otherwise, I added it as a new interval. Key Takeaways: - Sorting simplifies interval-based problems - Greedy approach helps in making optimal local decisions - Understanding overlap conditions is key This problem helped me understand how combining sorting and greedy logic leads to efficient solutions. #DSA #LeetCode #Intervals #Greedy #ProblemSolving #SoftwareEngineering #CodingJourney #100DaysOfCode #TechLearning #DeveloperJourney #Programming #Python #InterviewPreparation #CodingSkills #ComputerScience #JobReady #FutureEngineer #TechCareers #SoftwareDeveloper #LearnInPublic #OpenToWork

Everyone says “learn AI” But no one tells you WHAT to learn Here’s the actual stack 👇 🐍 Programming Language Start with Python Example: Easy syntax Example: Huge AI community 📚 Libraries These do the heavy lifting Example: TensorFlow Example: PyTorch 📊 Data Handling You need to work with data Example: Pandas Example: NumPy 📈 Visualization Understand what your model is doing Example: Matplotlib Example: Seaborn ⚙️ Tools & Platforms To build and run models Example: Jupyter Notebook Example: Google Colab ⚠️ Reality: You don’t need EVERYTHING Start small → go deep 🧠 Focus > Overwhelm Master basics first 🔜 Next: How AI is evolving (future + trends) #AI #ArtificialIntelligence #MachineLearning #Python #Developers #Coding #DataScience #Tech #LearnAI #SoftwareEngineering

All-in-One NumPy Guide. This guide includes: • Introduction to NumPy & array fundamentals • Indexing, slicing, and reshaping • Broadcasting and vectorization • Mathematical & statistical operations • And many more.... This “all-in-one” resource is designed to build a strong foundation in numerical computing and help apply NumPy effectively in Data Science and Machine Learning projects. """I’d really appreciate your feedback and would love to connect with professionals in the data field!""" #NumPy #Python #DataScience #MachineLearning #DataAnalytics #OpenToWork #Portfolio

Some problems are not about searching everywhere, but about searching smartly. Day 26/100 — Data Structures & Algorithms Journey Today’s Problem: Two Sum II (Input Array is Sorted) This problem helped me understand how sorting can simplify searching and improve efficiency. Approach: Since the array is already sorted, I used the Two Pointer technique instead of brute force. I placed one pointer at the beginning and another at the end of the array. By adjusting pointers based on the sum: If the sum is too small → move left pointer If the sum is too large → move right pointer If equal → solution found This approach avoids unnecessary checks and works efficiently in a single pass. Key Takeaways: Sorted data can unlock optimized solutions Two Pointer technique reduces complexity significantly Thinking smart is better than brute force Efficient algorithms improve performance and clarity This problem strengthened my understanding of pointer techniques and optimization strategies. #DSA #LeetCode #TwoPointers #ProblemSolving #SoftwareEngineering #CodingJourney #100DaysOfCode #TechLearning #DeveloperJourney #Programming #Python #InterviewPreparation #CodingSkills #ComputerScience #FutureEngineer #TechCareers #SoftwareDeveloper #LearnInPublic #OpenToWork

🎓 PhD in IT – Daily Learning Focus Digital transformation is reshaping how organizations and governments operate. Today’s focus areas: ✔ Learning Python for research and data analysis ✔ Exploring Digital Transformation strategies ✔ Understanding Public Sector Innovation Continuous learning and technology adoption are key to building smarter, more efficient systems. #PhDStudent #DigitalTransformation #ITResearch #Python #PublicSector #Innovation

Growth in DSA is not just about learning new concepts, but about reinforcing what you already know. Day 33/100 — Data Structures & Algorithms Journey Today was dedicated to revision, and it made me realize how important it is to revisit concepts to truly understand them. Instead of jumping into new problems, I focused on strengthening my foundation by going through previously learned patterns and solutions. Today’s Focus: - Revisiting key patterns like Two Pointers, Sliding Window, and DFS - Re-solving problems without looking at solutions - Understanding mistakes made earlier - Improving clarity and confidence in approach Why this matters? Because learning once is not enough — real understanding comes from repetition and refinement. Key Takeaways: Revision builds confidence and reduces mistakes Concept clarity improves with repetition Recognizing patterns becomes faster with practice Strong fundamentals make advanced problems easier Sometimes stepping back helps you move forward stronger. Consistency over intensity — always 🚀 #Day33 #DSA #LeetCode #ProblemSolving #SoftwareEngineering #CodingJourney #100DaysOfCode #TechLearning #DeveloperJourney #Programming #Python #InterviewPreparation #CodingSkills #ComputerScience #FutureEngineer #TechCareers #SoftwareDeveloper #LearnInPublic #Consistency