Python Revision Day 16: Strengthening Fundamentals

Day x of building in public 🔨(I don't remember tbh) Today felt like two different worlds colliding — 📚 College: Selection Sort, Bubble Sort, Insertion Sort ⚡ Home: CRUD operations on FastAPI One is about understanding HOW computers think. The other is about building things people can actually use. Both matter. Most people learn sorting algorithms and forget them. I'm learning them AND shipping code the same day. That gap — between knowing and doing — is where most people stay stuck. Not me. Not anymore. #100DaysOfCode #FastAPI #Python #DSA #BuildingInPublic #SoftwareEngineering

🚀 𝗗𝗮𝘆 𝟭𝟬/𝟯𝟬 — 𝗗𝗦𝗔 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲 Day 10 already — and this journey is starting to feel less about solving individual problems and more about recognizing patterns and choosing the right approach faster. Today’s focus was on sliding window techniques — understanding how adjusting a window dynamically can help track subarrays or substrings efficiently without rechecking everything from scratch. 🔎 𝗗𝗮𝘆 𝟭𝟬 𝗙𝗼𝗰𝘂𝘀 • Learning sliding window logic • Practicing dynamic range tracking • Solved: ✅ Maximum Average Subarray I ✅ Longest Substring Without Repeating Characters ✅ Permutation in String Still learning, still improving — one problem at a time. On to Day 11 💪 #DSA #Python #LeetCode #LearningInPublic #Consistency #SoftwareEngineering #ProblemSolving

🚀 𝗗𝗮𝘆 𝟴/𝟯𝟬 — 𝗗𝗦𝗔 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲 Starting Week 2 of this 30-day DSA journey, and it already feels like the focus is shifting from just solving problems to recognizing patterns faster. Today was about working with the two-pointer approach — learning how moving pointers from different directions can simplify problems that might otherwise need extra space or nested loops. 🔎 𝗗𝗮𝘆 𝟴 𝗙𝗼𝗰𝘂𝘀 • Understanding two-pointer techniques • Practicing cleaner comparisons and boundary logic • Solved: ✅ Two Sum II (Input Array Is Sorted) ✅ Valid Palindrome II ✅ Merge Sorted Array Still a lot to learn, but the thinking process is definitely getting sharper day by day. On to Day 9 💪 #DSA #Python #LeetCode #LearningInPublic #Consistency #SoftwareEngineering #ProblemSolving

feb-21-26 LeetCode 762 – Prime Number of Set Bits in Binary Representation Solved today’s problem focused on bit manipulation and prime checking! 🔹 Problem: Given two integers left and right, count how many numbers in that range have a prime number of set bits (1s) in their binary representation. 💡 Approach: Iterate through each number in the range. Count set bits using bitwise operations (& and right shift). Check whether the count of set bits is a prime number. Keep track of valid cases. 🧠 Concepts Used: Bit Manipulation Prime Number Checking Mathematical Optimization Simple problem on the surface, but a great way to strengthen understanding of binary representation and efficient computation. Consistency + Daily Practice = Growth 📈🔥 #LeetCode #BitManipulation #PrimeNumbers #Python #CodingPractice #ProblemSolving

AlhamduLillah! I am thrilled to share the release of my new notebook: A Complete Notebook on 5 Commonly Taught Searching Algorithms. I wrote this guide to provide a step-by-step roadmap for mastering data retrieval logic. It covers the A-to-Z of searching efficiency, moving from basic Linear Search to advanced logarithmic methods like Binary, Jump, Interpolation, and Exponential search. Each algorithm includes detailed mathematical complexity calculations, intuitive analogies, visual step-by-step mechanisms, and complete code in both C++ and Python. Download link: https://lnkd.in/gYwhkPFn

🔥 Day 97 — #100DaysOfLeetCode ✅ Problem: Count Binary Substrings (Easy) Today’s challenge was about counting substrings that contain equal numbers of consecutive 0’s and 1’s, where all 0’s and 1’s are grouped together. 🧠 Approach: Track length of current consecutive group. Track previous group length. Whenever character changes: → add min(prev_group, current_group) to result. Reset counters and continue. ⚡ Example "00110011" → Output = 6 ⏱ Complexity Time: O(n) Space: O(1) 💡 Key Insight: Valid substrings only form at boundaries between groups of 0’s and 1’s. Consistency builds mastery. #LeetCode #DSA #CodingJourney #Python #Algorithms

I’m currently working on a packet classification project and ran into a common hurdle: a lack of high-quality, public rulesets. To move forward, I decided to build my own dataset from scratch. 🛠️ My latest blog post breaks down the pipeline—from raw Wireshark captures to hardware-ready rules. While I started with academic research as a foundation, I developed my own custom path for data preparation and rule extraction to fit my specific needs. Check out the full workflow and code here: https://lnkd.in/dntK_Snv #PacketClassification #NetworkSecurity #MachineLearning #Python #DataScience

What Debugging My DSA Mistakes Taught Me Recently, I realized something: The real learning didn’t happen when I got the solution right. It happened when I got it wrong. - Popped from a stack twice in one line. - Confused floor division with truncation in Python. - Stored values instead of indices and broke duplicate cases. - Used Kadane where prefix sum was required. Each mistake exposed a hidden assumption. I stopped memorizing patterns and started understanding invariants. The biggest shift wasn’t solving harder problems, it was asking better “why” questions. #DSA #Algorithms #Python

🚀 Day-55 of #100DaysOfCode 📊 NumPy Practice – Row & Column Operations Today I practiced performing row-wise and column-wise operations on matrices using NumPy. 🔹 Concepts Practiced: ✔ 2D NumPy arrays ✔ np.max() with axis ✔ Matrix handling ✔ Vectorized computations 🔹 Key Learning: Understanding the axis parameter is very important in NumPy: axis=0 → column-wise axis=1 → row-wise NumPy makes matrix operations simple and efficient compared to traditional loops. Building strong fundamentals in numerical computing 💡🔥 #Python #NumPy #MatrixOperations #DataScience #100DaysOfCode #LearnPython #CodingPractice #PythonDeveloper

🔥 Day 30 of #100DaysOfCode 📌 LeetCode 26 – Remove Duplicates from Sorted Array Today’s problem focused on in-place array manipulation and strengthening the two-pointer technique. 🧠 Problem Summary Given a sorted array, remove duplicates such that each unique element appears only once. Return the count of unique elements (k). Important: Do it in-place with O(1) extra space. 💡 Key Insight Because the array is already sorted, duplicates are always adjacent. So instead of checking all elements repeatedly: 👉 Compare current element with previous one. 👉 If different → place it at the next unique index. This is where the Two Pointer Approach shines: Pointer i → traverses array Pointer k → tracks position of next unique element 📊 Complexity ⏱ Time: O(n) 📦 Space: O(1) Consistency > Motivation 30 Days Done. Still going strong 💪 #Day30 #LeetCode #DSA #100DaysOfCode #Python #CodingJourney