Data Science

This post, “Machine Learning Landscape 101”, will answer the following questions: The next post, “Machine Learning Landscape 102“, will answer the following questions: Together, these two posts offer a solid foundation for anyone looking to gain a deeper understanding of machine learning and its various applications. Let’s start. Machine Learning More engineering-oriented definition: A computer … Read more

When you start your journey to master AI, you encounter a term called model. What are models in AI? In AI, we talk about building models, which are shaped by cost functions to measure error. So what does this all mean? What are models? Models are an estimation of how reality works. These are not just part … Read more

A lack of symmetry is called skewness for data distribution. In other words, a departure from symmetry is called skewness. A distribution is simply a collection of data, or scores, on a variable. Usually, these scores are arranged in order from smallest to largest and then they can be presented graphically. Page 6, Statistics in … Read more

Through this blog, we will try to answer: “What is data distribution in machine learning?”. This blog post explores the concept of data distribution in data science. Understanding data distribution is a critical aspect of data analysis and visualization. A distribution is simply a collection of data, or scores, on a variable. Usually, these scores … Read more

Lorenz curve and Gini Coefficient are classic indicators in the field of economics. The Lorenz curve and Gini coefficient are important tools for professionals who work with data related to income inequality and wealth distribution, as well as for those who need to understand economic and social trends in their respective fields. We’re about to … Read more