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Machine learning is at the heart of modern data science. Whether you are forecasting demand or building classification models, choosing the right algorithm saves time and improves outcomes.
1. Linear Regression — ideal for predicting continuous values with clear linear relationships.
2. Logistic Regression — a go-to for binary classification problems.
3. Decision Trees — easy to interpret and useful for both classification and regression.
4. Random Forest — an ensemble method that reduces overfitting and boosts accuracy.
5. K-Means Clustering — perfect for discovering natural groupings in unlabeled data.
At Kryzotech, we teach these foundations with hands-on projects so learners can apply them in real jobs—not just in notebooks.