Day 8 of #100DaysOfLeetCode Problem: 9. Palindrome Number Category: Math / Two Pointers / Logic Today’s problem focused on determining whether an integer reads the same backward as forward — essentially checking if a number is a palindrome. 🧠 Key Learnings: Reversed the number mathematically using modulo and integer division. Avoided converting integers to strings, focusing purely on arithmetic logic. Understood how to handle special cases like negative numbers and numbers ending with zero. Strengthened my skills in digit manipulation and loop-based reversal logic. 🎯 Takeaway: Sometimes, avoiding built-in functions helps build a deeper understanding of fundamental logic — every digit and operation counts! #LeetCode #100DaysOfCode #ProblemSolving #CodingJourney #Math #LogicBuilding #Python #AIEngineer #Consistency

⚙️ Experiment 10: Support Vector Machine (SVM) using Python 🤖 In this lab, I explored the Support Vector Machine (SVM) algorithm — one of the most robust and widely used supervised learning models for classification and regression tasks. 🔍 Key learning outcomes: • Understanding the concept of hyperplanes and margins in classification • Implementing SVM using scikit-learn • Exploring linear and non-linear (kernel-based) decision boundaries • Performing hyperparameter tuning for improved accuracy • Visualizing classification boundaries and model performance This experiment helped me understand how SVM achieves high accuracy and generalization by optimizing the decision boundary, making it ideal for complex real-world datasets. 📁 Explore the repository here : 👉 https://lnkd.in/epWys7e7 #DataScience #MachineLearning #Python #SVM #Classification #KernelMethods #PredictiveModeling #DataAnalysis #LearningJourney #JupyterNotebook Ashish Sawant sir

🍁 Experiment 7: Simple Linear Regression using Python 🤖 In this lab, I explored the fundamentals of Simple Linear Regression, one of the most widely used techniques in predictive modeling. 🔍 Key learning outcomes: • Understanding the relationship between independent and dependent variables • Implementing linear regression using scikit-learn • Evaluating model performance using metrics like MSE and R² This experiment enhanced my understanding of how regression helps in predicting continuous outcomes and serves as a foundation for advanced machine learning algorithms. 📁 Explore the repository here : https://lnkd.in/epWys7e7 #DataScience #MachineLearning #Python #ScikitLearn #Statistics #DataAnalysis #PredictiveModeling #LinearRegression #LearningJourney #JupyterNotebook Ashish Sawant

Excited to share our recent work on Random Forest, a robust ensemble learning technique that enhances prediction accuracy and reduces overfitting by combining multiple decision trees. Key Highlights: Boosting accuracy through ensemble methods Reducing variance using bootstrap sampling Understanding feature importance for better insights Implemented using Python, leveraging libraries like Scikit-learn and TensorFlow Random Forest is one of the most versatile algorithms in machine learning - effective for both classification and regression tasks, and a great step toward mastering ensemble models! Team Members: M ARUN KUMAR REDDY (RA2311026010328) B THARUN SUJITH (RA2311026010348) B VENKATA ANIL KUMAR (RA2311026010353) A POOJA SAMANVITHA (RA2311026010363) P VENU GOPALA KRISHNA (RA2311026010368) #MachineLearning #RandomForest #ArtificialIntelligence #DataScience #Python #TeamWork #Al #DeepLearning #MLProjects #CSEAIML

Understanding Linear Regression (OLS) — From Math to Code! Recently, I studied Linear Regression, focusing on the Ordinary Least Squares (OLS) method to truly understand the mathematics behind it. I implemented OLS from scratch in Python and explored how linear algebra and calculus play a key role in deriving and optimizing the model. It was an insightful experience connecting theoretical concepts with practical implementation. 📂 Check out the project here: 👉 [GitHub Repository Link] #MachineLearning #DataScience #Python #LinearRegression #OLS #Mathematics #LinearAlgebra #Calculus #LearningByDoing

𝗗𝗮𝘆 𝟯𝟲 𝗼𝗳 #𝟭𝟴𝟬𝗗𝗮𝘆𝘀𝗢𝗳𝗖𝗼𝗱𝗲 Today, I solved 𝗦𝗲𝗮𝗿𝗰𝗵 𝗜𝗻𝘀𝗲𝗿𝘁 𝗣𝗼𝘀𝗶𝘁𝗶𝗼𝗻 — a practical variation of binary search. The goal was to find the index of a target in a sorted array, or the position where it should be inserted to maintain order. Using binary search, I efficiently located the correct spot in O(log n) time. The key was to track the first position where the element is greater than or equal to the target — which is exactly the insert position if the target isn’t found. This is a great example of how small tweaks to a classic algorithm can solve new problems elegantly. A useful technique for search, insertion, and maintaining sorted data dynamically! #Python #Algorithms #BinarySearch #LeetCode #Coding #ProblemSolving

Today's LeetCode problem was the foundational 509. Fibonacci Number. While there are faster ways to solve this, I focused on implementing the classic recursive solution. It's such a fundamental concept to understand, as it directly mirrors the mathematical definition: $F(n) = F(n-1) + F(n-2)$. It's a great reminder that coding is often about translating mathematical logic directly into code. The pursuit of efficiency (like using memoization next!) never stops, but understanding the basics is paramount. #LeetCode #Recursion #DSA #Algorithms #Python #ComputerScience

🗓 Day 2 / 100 – #100DaysOfLeetCode 📌 Problem 1636: Sort Array by Increasing Frequency The task was to sort an array such that elements with lower frequency appear first, and if two elements have the same frequency, the larger number comes first. 🧠 My Approach: Counted element frequencies using a hash map. Sorted the elements by ascending frequency and then by descending value. Reconstructed the array based on sorted frequency order. ⏱ Time Complexity: O(n log n) 💾 Space Complexity: O(n) 💡 Key Learning: This problem reinforced how powerful custom sorting logic can be in Python, especially when handling multiple sort priorities using tuple-based keys in sorting functions. Each day is helping me refine how I think about data organization, sorting, and frequency analysis — small steps that build strong foundations. #100DaysOfLeetCode #LeetCodeChallenge #Python #ProblemSolving #Algorithms #DataStructures #DSA #Sorting #CodingJourney #CodingChallenge #SoftwareEngineering #CompetitiveProgramming #CodeEveryday #LearningInPublic #DeveloperJourney #TechStudent #CareerGrowth #CodingCommunity #KeepLearning