Month: September 2019

Summarise Data in R – How to determine pearson spearman correlation in R

Summarise Data in R – How to determine pearson spearman correlation in R Determining the correlation between two variables is a common task in data analysis and statistics. Correlation is a measure of the relationship between two variables and it can be used to understand how changes in one variable are related to changes in …

Load Data in R – How to load data from mlbench library in R

Load Data in R – How to load data from mlbench library in R Loading data from the mlbench library in R is a useful way to access pre-built datasets that are included in the mlbench package. This library contains a wide range of datasets that can be used for different types of data analysis …

Load Data in R – How to load data from a url in R

Load Data in R – How to load data from a url in R Loading data from a URL in R is a common task in data analysis and machine learning. A URL (Uniform Resource Locator) is a web address that points to a specific resource on the internet, such as a file or a …

Load Data in R – How to load data from a R-dataset library

Load Data in R – How to load data from a R-dataset library Loading data from a R-dataset library is a useful way to access pre-built datasets that are included in various R packages. These libraries usually contain a wide range of datasets that can be used for different types of data analysis and machine …

Load Data in R – How to load data from a R library

Load Data in R – How to load data from a R library Loading data from a R library is a useful way to access pre-built datasets that are included in various R packages. These libraries usually contains a wide range of datasets that can be used for different types of data analysis and machine …

Load Data in R – How to load data from a csv file in R

  Load Data in R – How to load data from a csv file in R Loading data from a CSV file in R is a common task in data analysis and machine learning. CSV stands for Comma Separated Values and it is a plain text file format that is used to store data in …

Beginner’s Project on Regression in Python

Beginner’s Project on Regression in Python Machine learning regression is a type of machine learning where the goal is to predict a continuous value, such as a price or an age, based on a set of input features. It is used to model the relationship between a dependent variable and one or more independent variables. …

Beginner’s Project on Binary Classification in Python – Sonar Dataset

Beginner’s Project on Binary Classification in Python – Sonar Dataset Binary Classification is a type of machine learning problem where the goal is to classify instances into one of two classes. The Sonar Dataset is a popular dataset for binary classification problems, which is used to distinguish between metal cylinders and rocks from a sonar …

Beginner’s Project on Multi-Class Classification in Python

Beginner’s Project on Multi-Class Classification in Python Multi-class classification is a type of machine learning problem where the goal is to classify instances into one of multiple classes. This is different from binary classification, where the goal is to classify instances into one of two classes. There are several algorithms that can be used for …

How to save and load model with pickle

How to save and load model with pickle Saving and loading a model with pickle in Python is a way to preserve the trained model for future use. It allows you to save the model’s parameters, so you can use it later without the need to train the model again. This can save a lot …

How to save and load model with joblib

How to save and load model with joblib Saving and loading a model with joblib in Python is a way to preserve the trained model for future use. It allows you to save the model’s parameters, so you can use it later without the need to train the model again. This can save a lot …

How to do Random Search Cross Validation

How to do Random Search Cross Validation Random Search Cross Validation is a technique in machine learning that is used to find the best hyperparameters for a model, similar to Grid Search Cross Validation. Hyperparameters are the parameters of a model that are not learned from the data, such as the learning rate, the number …