🚢 Titanic Survival Prediction – Machine Learning & Streamlit ✅ Developed and deployed a user-friendly Streamlit web application to predict Titanic survival using Machine Learning, with clear model comparison and performance insights GITHUB LINK : https://lnkd.in/gaptG8kv STREAMLIT.IO LINK : https://lnkd.in/g6R6TwAd #DataScience #MachineLearning #Streamlit #Python #MLProject #LearningJourney #CareerRestart

Built a machine learning regression model to predict California housing prices using XGBoost and evaluated its performance through an actual vs predicted comparison. The project focuses on model training, performance evaluation, and a simple Streamlit interface for making predictions. Tech stack: Python, Pandas, NumPy, Scikit-learn, XGBoost, Streamlit. #MachineLearning #DataScience #Python #XGBoost #Regression #ScikitLearn #Streamlit #LearningByDoing #BuildInPublic

Built a Movie Recommender System using Machine Learning to understand how large-scale platforms personalize content. . . . Worked on data preprocessing, feature representation, and similarity-based recommendations using Python and Scikit-learn. Developed in Colab, modularized and tested in PyCharm. #MachineLearning #Colab #MovieRecommenderSystems #DataScience #Python #MLProjects #LearningByBuilding

🚀 Turning Student Data into Insights with ML! Analyzed how study hours and attendance affect exam performance 📊 Visualized trends and correlations, then applied an ML Linear Regression model using Python, Pandas, and Scikit-learn to predict student scores. This project demonstrates the workflow from raw data to ML predictions, combining data analysis, visualization, and model evaluation. Check out the code and notebook here: https://lnkd.in/g6kc3-QQ #MachineLearning #Python #DataScience #LinearRegression #DataVisualization #MLProjects #DataAnalysis

🚀 Top Python libraries for Data + ML (simple list) If you work with data, these tools cover almost everything: cleaning, charts, ML, APIs, and databases. If you’re starting: Pandas + NumPy → Matplotlib/Seaborn → Scikit-learn → PyTorch/TensorFlow ✅ Which library do you use the most? #Python #DataAnalytics #MachineLearning #DataScience #Programming #AI

🚀 House Price Prediction | Machine Learning Project Built a machine learning regression model to predict house prices using Python. Performed data cleaning, EDA, feature encoding, model training, and evaluation. Tech Stack: Python | Pandas | NumPy | Scikit-learn | Matplotlib | Jupyter Notebook GitHub Project: https://lnkd.in/ggrBHjNM #MachineLearning #DataScience #Python #MLProject #LearningJourney

Why Python for AI? Python offers a powerful ecosystem for building intelligent systems. With NumPy for numerical computing, Pandas for data preparation, and Matplotlib for visualization, it enables a smooth transition from raw data to actionable insights. #ArtificialIntelligence #Python #AI #DataScience #FutureofAi

From Code to Concept – Hands-on with Machine Learning! In this video, I’m working with Python and Machine Learning, implementing models using scikit-learn (including algorithms like Random Forest) to understand how data-driven solutions are built in practice. 💡 What this covers: Practical ML model implementation Clean, structured Python coding Applying theory to real-world problems I believe learning by doing is the best way to grow as a tech professional. Always exploring, experimenting, and improving 📈 Would love to hear your thoughts or suggestions! #MachineLearning #Python #DataScience #ArtificialIntelligence #CodingJourney #LearningByDoing #TechSkills #StudentDeveloper #Sklearn

Implemented Linear Regression from scratch using NumPy to strengthen my grasp of: • Feature scaling & normalization • Gradient descent optimization • Loss minimization • Model training vs inference Instead of relying on libraries, I focused on understanding how each component works under the hood — the kind of foundation that scales when moving to more complex models. This project reflects my transition from using machine learning tools to understanding them. Actively building, breaking, and improving. . . . #MachineLearning #DataScience #Python #NumPy #LearningJourney #StudentToProfessional #MLFoundations #CareerGrowth

⌛ This was 8 years ago, and if you try Python in Excel it feels like a feature they are still "considering." The real way to integrate Python and Excel is to move your Excel work to Python environments -- NOT jam python functions into your workbook. Python environments can handle larger datasets, faster processing, and more sophisticated AI. This is what we are building at Mito AI. The Excel-user front end for Python/AI workflows 🚀 #AI #Excel #Python #Data #DataScience