21 AUGUST 2023
By: Cyrus John
Machine learning has rapidly become an essential component across industries to make predictions, and automate tasks. Beginners should be able to grasp the fundamentals of algorithms. Here are the top 5 machine-learning algorithms that newcomers should know.
Linear regression stands as one of the simplest yet widely employed algorithms in machine learning. Its purpose lies in predicting a continuous target variable based on single or multiple input features. Its operation involves identifying the optimal-fit line that minimizes the disparity between predicted and actual values.
Decision trees present versatile algorithms suitable for both classification and regression tasks. They formulate a tree-like structure to make decisions rooted in input features, progressively segregating the data into subsets until a prediction emerges.
Neural networks reside at the cutting edge of contemporary machine learning and deep learning. Drawing inspiration from the human brain, they consist of interconnected nodes (neurons) that process and transform data.
SVM stands as a potent algorithm catering to classification and regression tasks alike. Its function entails identifying a hyperplane that optimally separates data points belonging to different classes, simultaneously maximising the margin between them.
PCA serves as a dimensionality reduction technique employed to transform high-dimensional data into a lower-dimensional space, all while retaining vital information. Its applications often encompass data visualization and enhancing the efficiency of other algorithms.