Learned KNN Algorithm and achieved 96.67% accuracy on Iris dataset

Today I explored how machine learning models handle categorical features — specifically, converting text data like city names into numbers the model can understand. Using the get_dummies() method in Pandas, I created dummy variables for the town column in my dataset, merged them back, and trained a Linear Regression model to predict house prices. It was cool to see how encoding categories correctly can change the model’s accuracy and make predictions more reliable. #MachineLearning #DataScience #Python #LinearRegression #Pandas #ScikitLearn #StudentLearning #AI

Excited to share my recent project comparing five popular classification algorithms — Logistic Regression, KNN, SVM, Decision Tree, and Random Forest! Through this experiment, I learned how different models handle data patterns and where each shines in terms of accuracy and performance. Ashish Sawant https://lnkd.in/eYH54psE #MachineLearning #DataScience #AI #Python #MLProject #Classification

Excited to share the ML pipeline I built to automate the full workflow — from preprocessing to model ensembling! Key Highlights: • KNNImputer + FunctionTransformer for handling missing values • OneHotEncoder for categorical encoding • RobustScaler for numerical scaling • Ensemble model using Random Forest, Gradient Boosting & XGBoost with a Voting Classifier This pipeline ensures clean data, consistent preprocessing, and efficient model training — all in one place! #MachineLearning #DataScience #Python #ScikitLearn #XGBoost #MLPipeline #AI #DataAnalytics #MLModels #FeatureEngineering #EnsembleLearning #CodingJourney #PortfolioProject

Kicking Off a New Series on AI Agents 🤖 Excited to share that I’ll be posting about AI Agents — from basics to advanced concepts — using the Agno Framework, which is super handy for beginners. We’ll learn step by step how Agentic systems work and build real examples along the way. 🚀 Show some love and support ❤️ — let’s make AI learning fun and practical! #AgenticAI #Agno #AIAgents #AIinProduction #LearningSeries #Python #AIEngineering #AI

#Day36 of #100DaysOfCode — 🔥 Today I learned LightGBM (Light Gradient Boosting Machine) LightGBM is a super-fast and high-performance boosting algorithm used for both classification and regression tasks. It uses a leaf-wise tree growth strategy, which makes it faster, more accurate, and memory-efficient. 💡 Today’s Learnings: ✔ LightGBM trains models extremely fast ✔ Great for multiclass datasets ✔ High accuracy with low memory ✔ Ideal for real-world ML solutions 🎯 Key Takeaway: LightGBM = Speed + Accuracy 🚀 #100DaysOfCode #MachineLearning #LightGBM #AI #DataScience #Python #PrathamSingla #MLJourney

Reflection Design Pattern in AI Agents Explained Simply! In this short tutorial, I walk through how reflection works in AI Agents. You’ll learn how this pattern forms the foundation for self improving AI systems, and how you can implement it yourself with just a few lines of code. 💻 GitHub repo: https://lnkd.in/gYiurHn9 #AI #MachineLearning #Agents #ReflectionPattern #Gemini #Python #AIDesignPatterns #LLM #GenerativeAI

Reflection Design Pattern in AI Agents Explained Simply! In this short tutorial, I walk through how reflection works in AI Agents. You’ll learn how this pattern forms the foundation for self improving AI systems, and how you can implement it yourself with just a few lines of code. 💻 GitHub repo: https://lnkd.in/gYiurHn9 #AI #MachineLearning #Agents #ReflectionPattern #Gemini #Python #AIDesignPatterns #LLM #GenerativeAI https://lnkd.in/gEWR2bVR

📘 #100DaysOfML – Day 02 Today’s focus was on Encoding Categorical Data — an essential step before feeding data into any Machine Learning model. 🔹 Explored Ordinal Encoding to convert text features like “category” into numerical values while keeping the order. 🔹 Learned about One-Hot Encoding — how it represents categories as binary vectors and why it’s better when the feature has no natural order. 🔹 Also got to know that One-Hot Encoding often returns a SciPy sparse matrix, which saves memory for large datasets! 🧠 Concepts are getting clearer step by step — can’t wait to move on to Feature Scaling & Transformation next! #MachineLearning #100DaysOfML #DataPreprocessing #AI #Python #LearningJourney