MACHINE LEARNING

🔍 What is Tableau? Tableau is a visual analytics tool that allows users to: Connect to multiple data sources Analyze large volumes of data Create interactive charts, graphs, and dashboards Share insights with others easily ✨ Why Tableau is So Popular? Tableau is widely adopted because of its: ✅ User-Friendly Interface No coding required—just drag fields and build visuals instantly. ✅ Interactive Dashboards Users can filter, drill down, and explore data dynamically. ✅ Fast Performance Handles millions of records efficiently. ✅ Multiple Data Connections Works with Excel, CSV, SQL, Google Sheets, cloud databases, and more. 🧩 Components of Tableau Understanding Tableau becomes easy once you know its main components: Dimensions – Categorical data (Name, Region, Category) Measures – Numerical data (Sales, Profit, Quantity) Shelves – Rows, Columns, Filters, Marks Worksheet – Area where visualizations are created Dashboard – Combination of multiple works...

 Machine Learning is a branch of Artificial Intelligence that enables computers to learn from data and improve their performance without being explicitly programmed . Why Do We Need Machine Learning? Traditional programming works well when rules are fixed. But real-world problems are complex and dynamic. Machine learning helps when: Data is huge Patterns are complex Rules change frequently Examples: Email spam detection Face recognition Product recommendations Weather prediction Types of Machine Learning 1️⃣ Supervised Learning The model learns from labeled data (input + correct output). Examples: Predicting marks based on study hours Email spam classification Common algorithms: Linear Regression Decision Tree Support Vector Machine 2️⃣ Unsupervised Learning The model works with unlabeled data and finds hidden patterns. Examples: Customer segmentation Grouping similar documents Common algorithms: K-Means Clustering Hie...