Cheat Sheet: 10 Must-Know Machine Learning Algorithms & When to Use Them

📝 Cheat Sheet: 10 Must-Know Machine Learning Algorithms & When to Use Them

📌 Here’s a quick overview of the most effective ML algorithms with practical use cases:

✅ Linear Regression
➡️ Predict continuous values (e.g., housing prices)

✅ Logistic Regression
➡️ Binary classification (e.g., spam detection)

✅ Decision Trees
➡️ Classification or regression with easy interpretation

✅ Random Forests
➡️ High accuracy for complex datasets

✅ Support Vector Machines (SVM)
➡️ Effective for non-linear classification

✅ K-Nearest Neighbors (KNN)
➡️ Best for small datasets in classification/regression

✅ Naive Bayes
➡️ Great for text classification and spam filters

✅ K-Means Clustering
➡️ Unsupervised pattern detection in unlabeled data

✅ Neural Networks
➡️ Best for images, voice, and natural language data

✅ Gradient Boosting Machines (GBM)
➡️ Powerful ensemble model for high-performance tasks

🔎 Quick Tips

✔️ Use KNN or Logistic Regression for small data
✔️ Choose SVM or Neural Networks for high-dimensional data
✔️ Need transparency? Go with Decision Tree or Logistic Regression

#MachineLearning #DataScience #AI #MLAlgorithms #ProgrammingValley