Linear

All you need to know about Linear Regression is here (including an application in Python)Image by Dariusz Sankowski on PixabayIf you’re approaching Machine Learning, one of the first models you may encounter is Linear Regression. It’s probably the easiest model to understand, but don’t underestimate it: there are a lot of things to understand and master.If you’re a beginner in Data Science or an aspiring Data Scientist, you’re probably facing some difficulties because there are a lot of resources out there, but are…

Linear optimization main concepts and implementation in PythonPhoto by Patrick Fore on UnsplashNumerical optimization is a fundamental tool in quantitative decision-making processes. To optimize a given goal, one must select values for interrelated decision variables under some prescribed set of circumstances. The format of the mathematical equations that describe the objective and the constraints of the problem is used to distinguish optimization problems between two major categories: Linear and Nonlinear…

Survival-horror games that allow me to fight back against whatever is trying to kill me are my jam. I like to exert a certain amount of control over my environment when trapped in frightful situations--it's how I cope. I don't dislike horror games where the main threat is an unkillable monster you just have to run away from. I'm just usually paralyzed with indecision and fear and wish I were literally anywhere else when trying to play them.It made checking out Amnesia: The Bunker at GDC particularly…

A Comprehensive Guideline on How to Implement Logistic Regression from ScratchPhoto by Rutger Leistra on UnsplashMotivationIf you read my previous articles on simple linear regression and multiple linear regression, you will get to know that linear regression predicts continuous value. But not all of our real-life prediction problems are associated with continuous values. Sometimes we need to classify an object or data based on its features. Linear regression algorithms can’t solve these problems. In this scenario,…

Part 6: A Gentle Introduction to Orthogonal VectorsPhoto by Karsten Würth on UnsplashThe previous article discussed Euclidean vector space, inner product, norm, distance, and angle in Rⁿ. This article will introduce orthogonal vectors, orthogonal projection, and linear transformation of vectors.Image 1. Orthogonal Vector in R² (Image by Author)Two vectors u and v are called orthogonal if u.v = 0If u and v are orthogonal vectors with Euclidean inner product, thenMaps a vector onto its orthogonal projection on a line or a…

To even better understand Gradient BoostingGradient Boosting is an ensemble method that is usually applied to decision trees. It is so often that we usually say Gradient Boosting to refer to Gradient Boosted Decision Trees. However, as an ensemble method, it is possible to apply it to other base models such as linear regression. But there is a trivial conclusion that you may already know:Gradient Boosted Linear Regression is, well, Linear Regression.But it is still interesting to implement it and moreover, we will do it…

When the eminent Australian anthropologist W. E. H. Stanner first published his essay on "The Dreaming" in 1956, there was increasing scholarly and popular interest in the complexity and duration of Australia's Indigenous cultures. That same year, an excavation by the archaeologist D. J. Mulvaney at Fromm's Landing in South Australia utilized radiocarbon dating…

Part 5: A Gentle Introduction to Euclidean Vector SpacePhoto by Karsten Würth on UnsplashMost of the time in both machine learning and deep learning, we are working with vectors. And the vector space model can represent the relationship between data as vectors. Moreover, from a geometric perspective, it is also able to compare the similarity of two vectors either using the distance between the two vectors (euclidean distance) or the angle between two vectors (cosine similarity).Let’s begin with the geometry of the vector…

Multiple Linear Regression from Scratch: Deep UnderstandingMultiple Regression with Two Features (x1 and x2) (Image By Author)MotivationWe, human beings, have been trying to create intelligent systems for a long ago. Because if we can automate a system, it will make our life easier and can be used as our assistant. Machine learning makes it happen. There are many machine learning algorithms for solving different problems. This article will introduce a machine learning algorithm which can solve the regression problem…

Photo by Michael Dziedzic on UnsplashMaster elements of linear algebra, start with simple and visual explanations of basic conceptsIntroductionIn this article, we continue the work we started in “Visualized Linear Algebra to Get Started with Machine Learning: Part 1”. We tackle new concepts of linear algebra in a simple and intuitive way. These articles are intended to introduce you to the world of linear algebra and make you understand how strongly the study of this subject and other mathematical subjects is related to…