Feature Engineering for Time Series
Feature Engineering for Time Series Data 1. Introduction to Feature Engineering in Time Series Feature engineering is a crucial step in time series forecasting and machine learning. It involves transforming….
Tag: Scikit-Learn
Implementing Logistic Regression
Logistic Regression is a supervised learning algorithm used for binary classification problems (e.g., spam detection, fraud detection). It predicts probabilities using the sigmoid function and maps outputs to either 0….
Implementing Linear Regression
What is Linear Regression? Linear Regression is a supervised learning algorithm used for predicting continuous values. It finds the best-fitting line (also called a regression line) to model the relationship….
Introduction to Machine Learning
Machine Learning (ML) is a subset of artificial intelligence (AI) that enables computers to learn patterns from data and make predictions or decisions without being explicitly programmed. It is widely….
Working with Scikit-learn
Scikit-learn (often abbreviated as sklearn) is one of the most popular machine learning libraries in Python. It provides simple and efficient tools for data analysis and modeling, including classification, regression,….
DBSCAN Clustering
DBSCAN Clustering: A Comprehensive Guide 1. Introduction to DBSCAN DBSCAN (Density-Based Spatial Clustering of Applications with Noise) is an unsupervised machine learning clustering algorithm that groups together points that are….
Gaussian Mixture Models
Gaussian Mixture Models (GMM) – A Comprehensive Guide 1. Introduction to Gaussian Mixture Models (GMM) A Gaussian Mixture Model (GMM) is a probabilistic clustering algorithm based on the assumption that….
K-Means Clustering
K-Means Clustering: A Comprehensive Guide 1. Introduction to K-Means Clustering K-Means Clustering is an unsupervised machine learning algorithm used for grouping similar data points into clusters. It aims to partition….
Gradient Boosting (XGBoost, LightGBM, CatBoost)
Gradient Boosting (XGBoost, LightGBM, CatBoost) in Machine Learning 1. Introduction to Gradient Boosting Gradient Boosting is a powerful ensemble learning technique used in machine learning for classification and regression tasks…..
k-Nearest Neighbors (k-NN)
k-Nearest Neighbors (k-NN) Algorithm in Machine Learning 1. Introduction to k-Nearest Neighbors (k-NN) k-Nearest Neighbors (k-NN) is a supervised learning algorithm used for classification and regression tasks. It is a….