Demand Forecasting
Demand Forecasting: A Comprehensive Guide 1. Introduction to Demand Forecasting Demand forecasting is the process of predicting future customer demand for a product or service using historical data, statistical models,….
Demand Forecasting: A Comprehensive Guide 1. Introduction to Demand Forecasting Demand forecasting is the process of predicting future customer demand for a product or service using historical data, statistical models,….
Autoregressive (AR) Models: A Comprehensive Guide 1. Introduction to Autoregressive (AR) Models Autoregressive (AR) models are one of the fundamental models used in time series forecasting. The AR model predicts….
ARIMA Models for Time Series Forecasting: A Comprehensive Guide 1. Introduction to ARIMA ARIMA (AutoRegressive Integrated Moving Average) is one of the most widely used statistical models for time series….
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….
Random Forests in Machine Learning 1. Introduction to Random Forests Random Forest is a Supervised Machine Learning algorithm that is used for both Classification and Regression tasks. It is an….
Decision Trees in Machine Learning 1. Introduction to Decision Trees A Decision Tree is a Supervised Learning algorithm used for both classification and regression problems. It mimics human decision-making by….
Logistic Regression in Machine Learning 1. Introduction to Logistic Regression Logistic Regression is a Supervised Learning algorithm used for classification problems. Unlike Linear Regression, which predicts continuous values, Logistic Regression….
Polynomial Regression in Machine Learning 1. Introduction to Polynomial Regression Polynomial Regression is an extension of Linear Regression that models the relationship between the independent variable (X) and the dependent….
Linear Regression in Machine Learning 1. Introduction to Linear Regression Linear Regression is one of the most fundamental and widely used supervised learning algorithms in machine learning. It is primarily….
Identifying Data Trends and Patterns: A Comprehensive Guide Introduction Identifying data trends and patterns is a crucial part of Exploratory Data Analysis (EDA) and plays a vital role in data….