Descriptive Statistical Analysis helps you to understand your data and is a very important part of Machine Learning. This is due to Machine Learning being all about making predictions. On the other hand, statistics is all about drawing conclusions from data, which is a necessary initial step. In this post you will learn about the most important descriptive statistical concepts. They will help you understand better what your data is trying to tell you, which will result in an overall better machine learning model and understanding.   Table of Contents: Introduction Normal Distribution Central ..read more

According to McKinsey, AI will create an estimated $13 trillion of GDP growth between now and 2030. As a comparison, the GDP of the entire United States of America was around 19 trillion in 2017. Leading AI scientists, like Andrew Ng, describe AI as the fourth industrial revolution or „the new electricity“. AI is undoubtedly a centerpiece of digital transformation and its application throughout the industry will dramatically change our world and how we do business. The problem is that many people want to participate in this AI-revolution but they are overwhelmed by its technological sophistica ..read more

Data Types are an important concept of statistics, which needs to be understood, to correctly apply statistical measurements to your data and therefore to correctly conclude certain assumptions about it. This blog post will introduce you to the different data types you need to know, to do proper exploratory data analysis (EDA) on your dataset, which is one of the most underestimated parts of a machine learning project. Table of Contents: Introduction to Data Types Categorical Data Nominal Ordinal Numerical Data Discrete Continuous  Interval Ratio Why Data Types are important? Statistic ..read more