We are generating data at an unprecedented pace right now. The scale and size of this data – it’s mind-boggling! Just check out these numbers:Facebook generates four petabytes of data in just one dayGoogle generates twenty petabytes of data every dayFurthermore, Large Hadron Collider (27 kilometers long most powerful particle accelerator of the world) generates one petabyte of...
Tuesday, January 17, 2023
Friday, January 6, 2023
Linear Regression
It is used to estimate real values (cost of houses, number of calls, total sales etc.) based on continuous variable(s). Here, we establish the relationship between independent and dependent variables by fitting the best line. This best fit line is known as the regression line and is represented by a...
MongoDB
MongoDB is an unstructured database. It stores data in the form of documents. MongoDB is able to handle huge volumes of data very efficiently and is the most widely used NoSQL database as it offers rich query language and flexible and fast access to data.Let’s take a moment to understand the architecture...
Wednesday, January 4, 2023
Machine Learning Algorithms
1. Supervised Learning AlgorithmsHow it works: This algorithm consists of a target/outcome variable (or dependent variable) which is to be predicted from a given set of predictors (independent variables). Using this set of variables, we generate a function that map inputs to desired outputs. The training process continues until the model achieves a desired level of accuracy on the training...
Monday, January 2, 2023
Components of a Time Series Forecasting in Python
1. Trend: A trend is a general direction in which something is developing or changing. So we see an increasing trend in this time series. We can see that the passenger count is increasing with the number of years. Let’s visualize the trend of a time series: ExampleHere the red line represents...