Coding for K – Means Algorithm using R & Python

We have seen Gradient decent using R & Python before now let us try a clustering algorithm with R & Python. I will briefly introduce the K means and the steps involved in it and implement these steps in both R & Python. […]

My Understanding of “What does Data science mean”?

A multidisciplinary fuse of data inference, algorithm development, and technology to solve analytically complex problems is known as Data science.
Data science is eventually about using this data in creative ways to generate business value.

Data Science is divided into two sub plots.
1. Discovery of data insight which helps quantitative data analysis to help steer strategic business decisions
2. Development of Data product, consists of algorithm solutions in production, opening at scale. For example, recommendation engines. […]

Gradient Descent Using R and Python

my previous blog, I presented syntactical differences and similar functions between R & Python. Now, I want to take it to next level and write some machine learning algorithms using both R and Python. Here, one may use direct functions from the packages available. However, here I am presenting the way to write your own functions for algorithms. In this series, I am starting with Gradient descent algorithm. I briefly explain, what is gradient descent. After that, I apply gradient descent algorithm for a linear regression to identify parameters. For illustration, I simulate data for simple linear regression. […]

R vs Python Function Comparison

We are going to compare Functions exist in both R and Python for same operations. And for this we took the Titanic dataset which contains the Passenger details.
Importing a CSV
Reading Data in both the languages is similar, but the only difference is for python we have to import pandas library for reading the Data. Once the importing is done we can look into the data by applying the below functions. […]

What skills are required to be a Data Scientist?

What skills are required to be a Data Scientist?

OR

Is strong mathematics background required to pursue a career as a data scientist?

We at Rang Technologies see a lot of questions like this. It’s hard when you’re trying to break into the field to know exactly how much math & stats you need. […]

Retail banking classification models

Now days the retail banking is one of the important business in banking sector, to improve the customer base, retain the existing customer, improve the banking revenue by offering different product to customer. […]

Batch forecasting – Structural thinking to develop R code

Forecasting is a common technique used in several companies to make predictions for the future. There are multiple methods of forecasting such as time series forecasting, multivariate forecasting, etc. In each of these methods there are techniques such as Moving Average (MA), ARIMA, ARMA, ARCH, GARCH, etc. […]

R Package dplyr Comparison of functions

In R, you can accomplish the same task in different ways.
This R document explains functions from R package–dplyr and in some places compares those functions with base functions. […]

Analytics Careers with SAS & R – Part 2

It’s been a month and what a month it has been! The new year is here already! One wonders where all the time has gone! I hope you also wonder on how far you have come in the process of learning and equipping yourself towards a successful career and life and take pride in it! This ‘present’ day’s effort will grant you the ‘gift’ of future! […]

Analytics careers using SAS and R : Part-1

Wikipedia describes Analytics as “the discovery and communication of meaningful patterns in data.” This comes in handy especially in areas rich with recorded information. Every day companies all over the world collect data about their customers and industries, simply as a routine activity during business transactions. […]