Category: Article

Machine Learning Applications: Natural Language Processing

Natural Language Processing is the ability of a computer to interpret human language. So NLP it's not only about text processing but also about understanding sentences and documents. By giving computers the ability to interpret human language, we can build better human-machine interfaces, extract information from non-structured data, and increment automation. Like Apple's Siri and … Continue reading Machine Learning Applications: Natural Language Processing →

Machine Learning Applications: Computer Vision

Computer Vision is a field of Artificial Intelligence that includes methods and techniques to enable computer programs to interpret and understand visual information, including images and videos. Typical Computer Vision tasks are image classification, object recognition, and Optical Character Recognition. The availability of large amounts of visual data, and computational power, combined with the advance … Continue reading Machine Learning Applications: Computer Vision →

When should we use Machine Learning to solve a problem?

We use Machine Learning for problems that traditional programming can't solve. In other words, we use Machine Learning for problems in which we can't infer a logical sequence of steps or rules to solve the problem. For example, let's say that we want to build a program to recognize the fruit contained in a picture. … Continue reading When should we use Machine Learning to solve a problem? →

The Best Algorithm to Start with Machine Learning

A good start point for Machine Learning is Linear Regression. By studying the Linear Regression algorithm, you will learn: Supervised LearningLoss FunctionsLoss Functions minimizationRegularization These concepts are not exclusive to Linear Regression. They apply to other learning algorithms as well. By creating and deploying Linear Regression models, you acquire engineering skills that are common to … Continue reading The Best Algorithm to Start with Machine Learning →

What are Machine Learning Tasks? (part 2)

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.

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 →