What are Machine Learning Tasks? (part 1)

Machine Learning is a set of computational techniques that allows us to extract patterns from data. In other words, these algorithms can learn the information contained in datasets like tabular data, text, images, or even videos. However, there is no universal algorithm capable of learning every pattern from every kind of data. Each machine learning algorithm solves a specific type of learning problem. We call machine learning tasks the particular learning problems solved by machine learning algorithms.

How to scale attributes with normalization and standartization

Attributes in different scales are common in Machine Learning projects. For example, a medical record dataset can include in the columns weight, height, and blood pressure. These attributes have different units of measure and vary in different intervals, making their comparison difficult. In these cases, we can apply a process called scaling to make this comparison easier. … Continue reading How to scale attributes with normalization and standartization

Introduction to Linear Regression With One Variable

In this post, we present Linear Regression analysis using a one variable example. Although real Linear Regression models use multiple input variables, the idea here is to keep the examples as simple and straightforward as possible, so you can focus on the intuition behind Linear Regression and don't get confused with too much data preparation or other details about tools and data manipulation. There are many algorithms to perform regression analysis, but Linear Regression is the simplest of them and the recommended algorithm to start with.