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Data Science

Welcome to our journal. Here you can find the latest company news and business articles

SUPERVISED LEARNING USING KNN 1
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Data Science

SUPERVISED LEARNING USING KNN 1

We have seen K-Means algorithm using R & Python before, now let me explain very basic classification algorithm with R. Briefly, I will introduce to K - Nearest Neighbour concept with various steps involved in it and how to implement those steps in R.K — NN algorithm:K-NN is one of the simplest supervised learning algorithm based on similarity functio read more..
K means Learning Algorithms Using R & Python
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Data Science

K means Learning Algorithms 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. K - means algorithm K-means is one of the simplest unsu read more..
Data Science: All you need to know
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Data Science

Data Science: All you need to know

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 read more..
Battle of the Programming Languages: R vs Python
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Data Science

Battle of the Programming Languages: R vs Python

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 CSVReading 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 read more..
Retail banking classification models
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Data Science

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.Today's world is digital, data is raising like population and you have to identify different customer in term of market opportunity, their risk and profit for bank.Of co read more..
Key of Developing R Code: Batch Forecasting
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Data Science

Key of Developing R Code: Batch Forecasting

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.There are several packages and algorithms available for forecasting in every d read more..
R Package dplyr Comparison of functions
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Data Science

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.   # import dplyr library# we are going to work with R in built dataset airqualitylibrary(dplyr)head(airquality)   read more..
Analytics Careers with SAS & R - Part 2
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Data Science

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!When we last communicated, we spoke of where read more..
Analytics careers using SAS and R : Part-1
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Data Science

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.World-class firms use this collected data and leverage on analytic read more..
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