Machine Learning – K-Nearest Neighbors (KNN)
The K-Nearest Neighbors (KNN) algorithm is one of the simplest and most intuitive machine learning algorithms. It can be used for both classification and regression tasks, making it a versatile …
Python
Machine Learning – AUC – ROC Curve
In machine learning, evaluating the performance of a classification model is crucial, especially when dealing with imbalanced datasets. The ROC Curve and AUC (Area Under the Curve) are two powerful …
Machine Learning – Cross-Validation
In machine learning, building a model that generalizes well to unseen data is a critical goal. Cross-validation is a robust technique for evaluating a model’s performance by testing it on …
Machine Learning – Bootstrap Aggregation (Bagging)
In machine learning, one of the challenges in building predictive models is managing variance and overfitting. Bootstrap Aggregation, commonly known as Bagging, is a powerful ensemble learning technique that addresses …
Machine Learning – K-Means
Clustering is a fundamental technique in unsupervised learning, and K-Means is one of the most popular clustering algorithms. It’s simple, efficient, and widely used for grouping data points into clusters …
Preprocessing – Categorical Data
In machine learning, data preprocessing is a critical step in building effective models. Categorical data, which represents variables with discrete categories, requires special handling to convert it into a format …
Machine Learning – Grid Search
Grid Search is a powerful technique for hyperparameter tuning in machine learning models. By systematically searching through a predefined set of hyperparameters, Grid Search ensures optimal performance for your model. …
Machine Learning – Logistic Regression
Logistic Regression is one of the most fundamental algorithms in machine learning for classification problems. Despite its name, Logistic Regression is not a regression algorithm but a classification technique. In …
Machine Learning – Hierarchical Clustering
Hierarchical Clustering is a popular unsupervised machine learning algorithm used for grouping data into a tree of clusters. This algorithm is highly intuitive and particularly useful when the number of …
Machine Learning – Confusion Matrix
Understanding the performance of a classification model is crucial in Machine Learning. The Confusion Matrix is a powerful tool that provides a comprehensive summary of your model’s predictions and their …