Top 8 Machine Learning Algorithms For Beginners

– Predicts continuous values based on input features. – Simple and widely used for regression tasks.

1: Linear Regression

– Predicts binary outcomes. – Used for classification tasks.

2: Logistic Regression

– Makes decisions based on input features. – Easily interpretable and versatile.

3: Decision Trees

– Ensemble of decision trees for improved accuracy. – Handles complex data and reduces overfitting.

4: Random Forest

– Creates hyperplanes to separate data into classes. – Effective for classification tasks in high-dimensional space.

5: Support Vector Machines (SVM)

– Classifies based on proximity to neighboring points. – Simple and intuitive for classification tasks.

6: K-Nearest Neighbors (KNN)

– Based on Bayes' theorem and conditional independence assumption. – Efficient for text classification and spam filtering.

7: Naive Bayes

– Mimics human brain with interconnected nodes. – Deep learning models for complex tasks like image recognition.

8: Neural Networks

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