We will be using Seaborn. Seaborn is a library that helps in visualizing data. It comes with customized themes and a high-level interface. This interface helps in customizing and controlling the kind of data and how it behaves when certain filters are applied to it.The ‘stripplot’ function is used when ... Read More

Machine learning deals with creating models from data, and generalizing on never before seen data. The data provided to a machine learning model as input should be such that it should be understood by the system properly, so that it can interpret the data and produce results.Visualizing data is an ... Read More

Machine learning deals with creating models from data, and generalizing on never before seen data. The data provided to a machine learning model as input should be such that it should be understood by the system properly, so that it can interpret the data and produce results.Seaborn is a library ... Read More

The process of converting a range of values into standardized range of values is known as normalization. These values could be between -1 to +1 or 0 to 1. Data can be normalized with the help of subtraction and division as well.Let us understand how L2 normalization works. It is ... Read More

We will be using the Seaborn library, that helps in visualizing data.When regression models are being built, multicollinearity is checked for. This is because we need to understand the correlation present between all different combinations of continuous variables. If multicollinearity exists between the variables, we have to make sure that ... Read More

Sometimes, it may be required to mathematically compute the inverse of a matrix and use the result of the operation for other purposes. Below are the steps to manually find the inverse of a matrix.Calculate the value of ‘minors’In this calculation, the values of current row and column are ignored, ... Read More

Let us understand how the slicing operator ‘:’ can be used to access elements within a certain range.Example Live Demoimport pandas as pd my_data = [34, 56, 78, 90, 123, 45] my_index = ['ab', 'mn' ,'gh', 'kl', 'wq', 'az'] my_series = pd.Series(my_data, index = my_index) print("The series contains following elements") print(my_series) ... Read More

The determinant value can be calculated on a matrix or on an array that has more than one dimension.It may sometimes be required to understand the marix/array better. This is where the determinant operation would be needed.SciPy offers a function named ‘det’ that is present in the ‘linalg’ class which ... Read More

The process of converting a range of values into standardized range of values is known as normalization. These values could be between -1 to +1 or 0 to 1. Data can be normalized with the help of subtraction and division as well.Data fed to the learning algorithm as input should ... Read More

Feature scaling is an important step in the data pre-processing stage in building machine learning algorithms. It helps normalize the data to fall within a specific range.At times, it also helps in increasing the speed at which the calculations are performed by the machine.Why it is needed?Data fed to the ... Read More