These are 8 of the most important supervised machine learning algorithms you should know. 🧠 1️⃣ Linear Regression: Predicts a continuous value by modeling a linear relationship between inputs and the target. 2️⃣ Logistic Regression: Predicts the probability of a class, making it a common choice for classification. 3️⃣ K-Nearest Neighbors: Makes predictions based on the labels or values of nearby examples. 4️⃣ Support Vector Machine (SVM): Finds a decision boundary that separates classes while maximizing the margin between them. 5️⃣ Decision Tree: Makes predictions through a sequence of feature-based decisions. 6️⃣ Random Forest: Combines many decision trees to produce a more robust prediction. 7️⃣ Boosting: Builds an ensemble sequentially, with each new model focusing on errors from the existing ensemble. 8️⃣ Neural Network: Learns complex, non-linear relationships through layers of interconnected neurons. #SupervisedLearning #MLAlgorithms #PredictiveModeling #DataScienceEducation #MachineLearning