Regression

You can find the full code on my GitHub account. I. Introduction Estimating the market value of football players using machine learning serves various purposes and provides numerous benefits to various stakeholders in the football industry: Player evaluation: Clubs, agents and investors need accurate estimates of a player’s market value to make…

Understanding the Inner Workings of Ordinary Least Squares for Effective Predictive Modeling — Introduction Linear regression is a fundamental tool in the field of statistics and machine learning, allowing us to uncover patterns, make predictions, and gain insights from data. At the heart of this powerful technique lies Ordinary Least Squares (OLS), a method used to estimate the parameters of a linear regression model…

One of the main goals of humanity has been to try to understand the relationships between different things. To do so, people have been using math to help them in this task. One approach that people like the most is trying to fit this relationship as if it were linear…

In the last charpter, we investigated the relationships between features in a dataset containing information from cars of different brands. The main goal was to fit a multivariate regression model and analyze the results. After fitting the model and examining the summary, we are now going to tackle one of…

Linear Regression is a statistical modelling technique used to discover the relationship between a dependent variable and an independent variable. It is simple yet powerful and is one of the most used algorithms in Machine Learning. …

One of the most important problems in regression analysis is the selection of predictors in the model. The resoson behind this is we are often not satisfied with the least squares estimates. First of all the least squares estimates have low bias and large variance. Since we sacrifice bias to…

Below I outline seven important steps that start with thinking about ML Model building to fully deploying a ML model. Contextualise and Understand the Problem This is the first step in getting a better idea of what is trying to be achieved by building a ML model. Clearly define the…

In the vast realm of regression analysis, decision trees have long been revered for their interpretability and ability to capture intricate relationships within data. …

In this blog post, we will learn how to make classification and regression predictions with a finalized machine learning model in the scikit-learn Python library. Scikit-learn is a popular and powerful library that provides a variety of tools for predictive data analysis, such as supervised and unsupervised learning algorithms, model…