What are Window Functions? Window functions are functions that allow you to perform calculations over a subset of data within a larger table. They are different from regular aggregate functions like SUM and AVG, which calculate a single value for an entire column. Window functions, on the other hand, calculate a value for each row based on a specified window or subset of rows. This may sound simple, yet confusing. Let’s break it down into smaller pieces and gain a better understanding.

SQL subqueries are queries that are embedded within another query. They are used to retrieve data that will be used in the main query, either as a filter condition, a column value, or a table source. Subqueries can be used in multiple contexts like SELECT, INSERT, DELETE etc In this post, we will use the Sakila sample database provided by MySQL Common uses cases Here are some of the most common use cases of subqueries in a SELECT context:

As we try to make sense of the data stored in a database, we may need to look at multiple tables that hold different pieces of information. For example, we may have one table with customer information, another with product information, and yet another with order details. In order to see the bigger picture and understand how everything fits together, we use SQL joins to combine the data from these tables.

Linear Regression is the most simple and basic model in machine learning. It may seem dull compared to advanced machine learning models, yet it is still a widely used statistical learning model. The importance of having a good understanding of linear regression before studying more complex methods cannot be overstated. Definition Liner Regression is a linear model that assumes a linear relationship between the input variables($X$) and output variable($Y$). Mathematically, this linear relationship can be represented as $$Y \approx \beta_0 + \beta_1X $$ In above equation, $\beta_0$ and $\beta_1$ are two unknown constants that represent the intercept and slope terms of the linear model.

Machine Learning, Artificial Intelligence, Data Science, Deep Learning are the buzzwords these days. All of these words are used interchangeably, but there are slight differences among them. Artificial intelligence includes subfields such as machine learning, deep learning, and neural networks. Deep learning, on the other hand, is a branch of machine learning, and neural networks is a branch of deep learning. Deep learning and Machine learning differs on how each algorithm learns.