NumPy Practice: Row & Column Operations with Python

🚀 Day-68 of #100DaysOfCode 📊 NumPy Practice – Chessboard Pattern Today I created a chessboard pattern using NumPy. 🔹 Concepts Practiced ✔ Matrix creation using np.zeros() ✔ Advanced array slicing ✔ Pattern generation using NumPy 🔹 Key Learning NumPy slicing allows creating complex patterns efficiently without loops. This type of matrix manipulation is useful in image processing and grid-based computations. Building deeper understanding of NumPy array operations 🚀 #Python #NumPy #MatrixManipulation #PythonProgramming #100DaysOfCode #LearnPython

🚀 Day-66 of #100DaysOfCode 📊 NumPy Practice – Image Matrix Manipulation Today I simulated a grayscale image using NumPy and performed a simple brightness adjustment. 🔹 Concepts Practiced ✔ Random matrix generation ✔ Array arithmetic operations ✔ Pixel value clipping using np.clip() ✔ Understanding image data as matrices 🔹 Key Learning Images in computer vision are essentially NumPy matrices, where each element represents a pixel intensity. NumPy makes it easy to manipulate these values efficiently. Exploring how NumPy connects with image processing and computer vision 📸✨ #Python #NumPy #DataScience #ComputerVision #MachineLearning #100DaysOfCode

🚀 Day-56 of #100DaysOfCode 📊 NumPy Practice – Finding Unique Values & Frequency Today I practiced identifying unique elements and counting their occurrences using NumPy. 🔹 Concepts Practiced: ✔ np.unique() ✔ Frequency counting ✔ Handling duplicate values ✔ Efficient array analysis 🔹 Key Learning: Using return_counts=True makes frequency analysis simple and efficient without loops — very useful in data preprocessing. Slowly stepping into data analysis concepts using NumPy 💡🔥 #Python #NumPy #DataAnalysis #ArrayOperations #100DaysOfCode #LearnPython #CodingPractice #PythonDeveloper

🌟 Day 45 | Strengthening graph fundamentals 🌿 Today, I explored different ways to represent graphs in Python: • Adjacency Matrix using 2D lists • Adjacency List using lists of lists • Adjacency Dictionary using Python dict for dynamic graphs Also understood their real-world use cases and how each representation impacts memory and efficiency. Choosing the right representation is key to solving graph problems effectively ✨ #DSA #Graphs #DataStructures #PythonProgramming #ProblemSolving #CodingPractice #ComputerScience #Btech

📌 Creating Arrays with NumPy NumPy provides a powerful object called ndarray (N-dimensional array) used for storing and working with data efficiently. An array is a collection of elements stored in a single variable, and in NumPy arrays are homogeneous (all elements are usually of the same data type). Example steps: 🔹 Install NumPy pip install numpy 🔹 Import NumPy import numpy as np 🔹 Create an array arr = np.array([1,2,3,4,5]) This creates a NumPy array, and its type will be numpy.ndarray. NumPy arrays are faster and more efficient for numerical operations compared to regular Python lists. #Python #NumPy #DataAnalytics #Programming #LearningPython

Most people use scipy.optimize and move on. I wanted to understand what's actually happening underneath. So I built three optimization algorithms from scratch in Python, no external solvers, just NumPy: → Truncated Newton: finds local minima efficiently, approximating the Hessian without ever computing it fully → Sequential Penalty: handles constraints by turning them into a penalty, the more you violate them, the harder the algorithm pushes back → Filled Functions: the interesting one. When you're stuck in a local minimum, it builds an artificial "hill" on top of it to force the search elsewhere, that's how you find the global optimum Tested on 20+ benchmark problems. It works. In collaboration with Paolo Pascarelli and Silvia Alonzo Full code + writeup below 👇 https://lnkd.in/d8TwHtcS #python #optimization #numericalcomputing

🚀 Day-76 of #100DaysOfCode 📊 NumPy Practice – Palindrome Array Check Today I worked on checking whether an array is a palindrome using NumPy and basic logic. 🔹 Concepts Practiced ✔ Array traversal ✔ Index comparison ✔ Logic building without shortcuts 🔹 What is a Palindrome? An array is called a palindrome if it reads the same forward and backward. 🔹 Key Learning Instead of using built-in shortcuts, I focused on building the logic manually by comparing elements from both ends. This approach helps strengthen problem-solving and interview skills. Consistency + Logic Building = Growth 🚀  #Python #Numpy #ProblemSolving #CodingChallenge #100DaysOfCode #LearnPython

🚀 Day 55 of #100DaysOfCode Solved LeetCode 350 – Intersection of Two Arrays II today! 🔍 Problem Insight: Given two arrays, we need to return their intersection such that each element appears as many times as it occurs in both arrays. 💡 Approach Used: - Used "Counter" (hash map) to store frequency of elements from first array - Traversed second array and matched elements - Reduced count after every match to handle duplicates correctly ⚡ Why this works: Efficient frequency tracking avoids nested loops and reduces time complexity. 🧠 Complexity: - Time: O(n + m) - Space: O(n) ✅ Key Learning: Hashing + frequency counting is powerful for problems involving duplicates and intersections. 🔥 Consistency is the key — showing up every day! #DSA #LeetCode #Python #CodingJourney #PlacementPrep #SoftwareEngineering #100DaysOfCode

🚀 Day 42 / 200 – Minimum Window Substring (Hard) Solved LeetCode 76 – Minimum Window Substring today! 💪 This problem was a great test of Sliding Window + HashMap concepts. The challenge was to find the smallest substring that contains all characters of another string (including duplicates). 🔎 Key Learnings: Mastered the two-pointer (left & right) sliding window technique Used frequency counters to track required characters Optimized window shrinking to ensure minimum length Improved understanding of handling duplicate character constraints ✅ 268 / 268 test cases passed ⚡ Runtime: 75 ms 🐍 Language: Python Problems like this strengthen real-world problem-solving skills and improve optimization thinking. Consistency > Motivation. 200 Days. No excuses. 💯 #Day42 #200DaysChallenge #LeetCode #Python #DataStructures #Algorithms #SlidingWindow #ProblemSolving #CodingJourney

Inside the exact prompt sent to Claude Opus 4.6: “Can you use any resources you want, including Python, to create a short ‘YouTube Poop’ video and render it with FFmpeg? Add a personal touch, it should capture what it feels like to be an LLM.” Credit: josephdviviano on X Want to learn more about AI? 👉🏻 https://shorturl.at/idMUk