# Tag: dataScience

- Multiple Linear Regression With Python (12 Jun 2019)

Regression is a machine learning model which we can use to predict values by using previously observed data. In simple linear regression, we had to use only one independent variable for the prediction. but in the real world often a dependent variable is dependent upon several variables.
- Simple Linear Regression With R (05 May 2019)

Regression models are used to predict real values such as salary, spending, income. Simple linear regression is a model of regression which is used to identify the correlation between two variables and possibly predict the dependent variable by using the independent variable.This will enable us to establish a relationship between two attributes such as Income and Spending and we can use what we know about the relationship to forecast unobserved values.
- Data Pre-Processing With R (04 May 2019)

Before feeding our dataSet into a machine learning algorithm it's absolutely necessary to pre-process the data where we should clean and re-shape our data to get the maximum performance from our machine learning models. In this post, I will go through a set of procedures which you can use to pre-process a data set.

## Archive

`programming`

`web`

`machineLearning`

`aws`

`javascript`

`dataScience`

`react`

`r`

`csharp`

`typescript`

`thoughts`

`testing`

`s3`

`redux`

`rdbms`

`python`

`nuget`

`micro-service`

`lambda`

`jest`

`genie`

`dotnet`

`cloud`

`bigdata`

`angular`