Python Signal Processing Course: Learn by Doing

Signal Processing is attracting many students from computer science, but the challenge is that they need to spend more time understanding the computing infrastructure on which their algorithms run. All the best to Dan Boschen

Built a QR Code Reader & Generator using OpenCV today. The reader works in real-time using camera input, while the generator creates QR codes for custom data. While working on this, I also explored how OpenCV handles QR detection and understood the need for additional libraries when it comes to QR generation. This small project helped me strengthen my understanding of computer vision workflows, real-time processing, and integrating multiple tools together. Project: opencv-qr-system GitHub: https://lnkd.in/gfQ-A-Qy #OpenCV #ComputerVision #Python #Projects #LearningByDoing

🚀 Excited to share my latest project: File System Recovery and Optimization Tool In this project, I designed a system that: ✔️ Simulates real-world file system operations ✔️ Recovers data after crashes or accidental deletion ✔️ Optimizes storage using efficient allocation techniques ✔️ Reduces fragmentation and improves performance 💡 Key Learning: Bridged the gap between Operating System theory and practical implementation 🔧 Tech Used: Python, OS concepts, file handling Would love your feedback! 👇 #OperatingSystems #Projects #ComputerScience #DataRecovery #TechProjects #StudentDeveloper #LearningByDoing

Excited to share my latest project: Page Replacement Algorithm Simulator Built using Python, this interactive application visualizes how memory management works in Operating Systems by simulating FIFO, LRU, LFU, and Optimal algorithms. It provides step-by-step execution, real-time metrics (page faults, hits, hit ratio), and insightful graphical analysis using matplotlib. With a clean dark-themed UI, playback controls, and comparative dashboards, the project transforms theoretical concepts into an intuitive, hands-on learning experience. This project helped me strengthen my understanding of OS concepts while also enhancing my skills in Python, GUI development, and data visualization. #Python #OperatingSystems #Algorithms #Projects #Learning #SoftwareDevelopment

🚀 Mini Project: Temperature Conversion Program (Python) I recently built a simple yet interactive temperature conversion program using Python that can convert between Celsius, Reaumur, Fahrenheit, and Kelvin. This project features: Menu-based user interface Input validation using exception handling Clean and formatted output History tracking using list data structure Through this project, I strengthened my understanding of fundamental programming concepts such as conditionals, looping, functions, and basic data handling. It may be a small project, but it’s a meaningful step in improving my programming logic and problem-solving skills. Looking forward to building more projects and continuously learning 🚀 #Python #Programming #MiniProject #LearningByDoing #IndustrialEngineering

Day 50: Target Sum Task: Given an array of integers and a target value, find the number of ways to build an expression by assigning either a '+' or '-' to each integer so that they evaluate to the target. Solution: Math Reduction + 1D Dynamic Programming. This looks like a backtracking problem at first, but it can actually be mathematically reduced to the classic "Subset Sum" problem! If we group all the positive numbers into subset S1 and the absolute values of the negative numbers into subset S2, we know two things: S1 - S2 = target S1 + S2 = total_sum By combining these equations, we get 2 * S1 = total_sum + target, meaning the required sum of our positive subset (S1) must be exactly (total_sum + target) / 2! Instead of simulating every single +/- combination (which is extremely slow), this mathematical trick transforms the problem. I just used a 1D DP array to count how many subsets add up to this exact target. This optimizes the time complexity and keeps the auxiliary space super lightweight! #geekstreak60 #npci #codingchallenge #dailylearning #programmer #python #dynamicprogramming #dp #algorithms

🧩 DSA Breakdown: Insert Interval One of those problems that looks scary at first, but once you see the pattern — it clicks instantly. The problem: Given a sorted list of non-overlapping intervals, insert a new interval and merge if needed. The trick? Just think in 3 phases: 1️⃣ Add all intervals that END before the new one starts → no overlap, safe to add 2️⃣ MERGE all intervals that overlap → keep expanding the new interval's boundaries 3️⃣ Add everything remaining → they start after the new interval ends ✅ Time: O(n) — single pass ✅ Space: O(n) Currently grinding DSA one problem at a time 💪 If you're on the same journey, let's connect! #DSA #CodingInterview #Python #LeetCode #Programming #100DaysOfCode

I recently revisited one of my first-year Python projects — an Analog Clock built using the Turtle module. At that time, the goal was simple: apply basic programming concepts to create something visual and functional. This project helped me understand how real-world systems can be translated into code using logic, mathematics, and real-time updates. The video shows the clock running in real time. Key learnings: • Working with Python Turtle for graphical rendering • Handling real-time updates using the time module • Using mathematical calculations for angle-based positioning This was a small but important step in building my programming foundation. 🔗 GitHub Repository: https://lnkd.in/gzRphNY4

Moving from theory to real-time monitoring. In a production CV pipeline, "accuracy" isn't a static number. Lighting shifts and hardware wear-and-tear cause the model's confidence to drift. Today I implemented a Running Mean and Standard Deviation logic to catch these anomalies on the fly. Instead of waiting for a total system failure, this script flags any confidence score that drops more than 2 standard deviations (2-sigma) below the historical average. It’s a direct translation of statistics into a fail-safe for my thesis project. Solving for reliability, not just "passing" tests. Logic is up on GitHub: https://lnkd.in/ghBQDJVg #MachineLearning #MLOps #Statistics #Python #BuildInPublic #AgriTech

Built something that actually recognizes me. I developed a Face Recognition Attendance System using Python and OpenCV that works in real-time. • Detects faces using Haar Cascade • Trains on custom dataset using LBPH algorithm • Recognizes individuals with confidence scoring • Automatically logs attendance with timestamps What started as a simple idea turned into solving real challenges — handling bad data, improving accuracy, and making the system reliable. This project pushed me from just learning concepts to actually building systems. Next: making it product-level with GUI and database. #Python #OpenCV #ComputerVision #MachineLearning #Projects #LearningByDoing