Analyzing Soccer Results with Power BI
Business Intelligence turns data into information and information into knowledge for business decisions. See it in action analyzing Spanish soccer results with Power BI.
Articles
Selecting the Optimal Number of Clusters
One of the problems when applying a Clustering method (K-means or EM) is choosing the number of Clusters. Learn the elbow method, dendrograms and the gap.
Expectation-Maximization in Python and Scikit-learn, with Examples
Expectation-maximization is a statistical clustering method similar to K-means, but with a probabilistic approach. Learn how it works with Python examples.
K-means in Python and Scikit-learn, with Examples
K-means is a clustering method that splits objects into K groups by minimizing inertia. Learn how it works and how to use it in Python with scikit-learn.
What Is Clustering?
Clustering is the task of grouping a set of unlabeled objects into subsets of objects called Clusters. Learn how it differs from classification.
What Is Machine Learning?
Machine Learning (ML) is a branch of Artificial Intelligence (AI) that aims to build systems able to learn on their own from a data set, without explicit programming.
Reading and Writing Files in Python, with Examples
In this tutorial you'll learn how to read and write files in Python, one of the most useful and commonly used tasks when programming. Examples included.
Singleton Pattern in Java, with Examples
Learn the Singleton design pattern in Java: a software engineering pattern that limits the creation of objects of a class to one, with code examples.
MySQL Database Course – Part V – (Video) “Group By”
The "Group By" statement groups identical values in a table. Learn how it works with COUNT, SUM, MAX and MIN in this video tutorial and step-by-step examples.
Pandas in Python, with Examples – Part I – Introduction
Pandas is a Python library for data analysis that provides flexible data structures that let you work with your data very efficiently. Start here.
Pandas in Python, with Examples – Part II – Reading/Writing, Merge & GroupBy
In this tutorial we show some of the operations and features the Pandas library offers for working with DataFrames, including I/O, merge and groupby.
Pandas in Python, with Examples – Part III – Pivot_table
Learn how to use pandas pivot_table in Python with practical examples: group, aggregate and analyze the MovieLens dataset like in a spreadsheet.