Publications by suresh kumar Gorakala
Time Series Analysis using R – forecast package
In today’s blog post, we shall look into time series analysis using R package – forecast. Objective of the post will be explaining the different methods available in forecast package which can be applied while dealing with time series analysis/forecasting. What is Time Series?A time series is a collection of observations of well-defined data...
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Basic recommendation engine using R
In our day to day life, we come across a large number of Recommendation engines like Facebook Recommendation Engine for Friends’ suggestions, and suggestions of similar Like Pages, Youtube recommendation engine suggesting videos similar to our previous searches/preferences. In today’s blog post I will explain how to build a basic recommender ...
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Regression Analysis using R
What is a Prediction Problem?A business problem which involves predicting future events by extracting patterns in the historical data. Prediction problems are solved using Statistical techniques, mathematical models or machine learning techniques.For example: Forecasting stock price for the next week, predicting which football team wins the world...
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Exposing R-script as API
R is getting popular programming language in the area of Data Science. Integrating Rscript with web UI pages is a challenge which many application developers are facing. In this blog post I will explain how we can expose R script as an API, using rApache and Apache webserver. rApache is a project supporting web application development using the ...
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Introduction to Logistic Regression with R
In my previous blog I have explained about linear regression. In today’s post I will explain about logistic regression. Consider a scenario where we need to predict a medical condition of a patient (HBP) ,HAVE HIGH BP or NO HIGH BP, based on some observed symptoms – Age, weight, Issmoking, Systolic value, Diastolic value, RACE, et...
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Data Mining Standard Process across Organizations
Recently I have come across a term, CRISP-DM – a data mining standard. Though this process is not a new one but I felt every analyst should know about commonly used Industry wide process. In this post I will explain about different phases involved in creating a data mining solution. CRISP-DM, an acronym for Cross Industry Standard Process for D...
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Item Based Collaborative Filtering Recommender Systems in R
In the series of implementing Recommendation engines, in my previous blog about recommendation system in R, I have explained about implementing user based collaborative filtering approach using R. In this post, I will be explaining about basic implementation of Item based collaborative filtering recommender systems in r. Intuition:Item based Coll...
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Data Science with R
As R programming language becoming popular more and more among data science group, industries, researchers, companies embracing R, going forward I will be writing posts on learning Data science using R. The tutorial course will include topics on data types of R, handling data using R, probability theory, Machine Learning, Supervised – unSupervi...
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Basic Data Types in r
As part of tutorial series on Data Science with R from Data Perspective, this first tutorial introduces the very basics of R programming language about basic data types in R.What we learn:Assignment OperatorNumericIntegerComplex numberlogicalCharacterFactorVectorData FrameAfter the end of the chapter, you are provided with R console so that you c...
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Principal Component Analysis using R
Curse of Dimensionality:One of the most commonly faced problems while dealing with data analytics problem such as recommendation engines, text analytics is high-dimensional and sparse data. At many times, we face a situation where we have a large set of features and fewer data points, or we have data with very high feature vectors. In such scena...
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