Cache-Master

This project focuses on creating functions in R that can cache potentially time-consuming computations. It explores the concept of scoping rules in the R language and demonstrates how they can be manipulated to preserve state within an R object.

Example: Caching the Mean of a Vector

In this, provided two functions, makeVector and cachemean, to create a special object that stores a numeric vector and caches its mean. The makeVector function creates a unique "vector" object, while the cachemean function calculates the mean of the vector, utilizing caching to avoid redundant computations.

Objective: Caching the Inverse of a Matrix

The objective is to write two functions, makeCacheMatrix and cacheSolve, that cache the inverse of a matrix. The makeCacheMatrix function creates a special "matrix" object that can cache its inverse, and the cacheSolve function computes the inverse of the matrix, utilizing caching to improve performance.

Getting Started

To get started with the project, follow these steps:

1. Clone the repository: git clone https://github.com/akshupande/Cache-Master.git
2. Navigate to the project directory: cd Cache-Master

Usage

Functions can be used in R code by following these steps:

1. Source the R script containing the functions: source("caching_functions.R")
2. Create a special vector object: v <- makeVector()
3. Set the value of the vector: v$set(c(1, 2, 3, 4, 5))
4. Calculate the mean of the vector, utilizing caching: cachemean(v)
5. Retrieve the cached mean: v$getmean()

Contributing

Contributions are welcome! If you find any issues or have suggestions for improvements, please submit a pull request.