Stationarity in Time SeriesThe first step for any time series analysis is to make the data set stationary. Everyone knows that stationarity means a near to constant mean and variance across time.Stationarity in Time Series
Continue readingLabel Encoder and One Hot Encoding
TheDataMonk
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Python , Uncategorized
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In our datasets we can have any sort of data, we can have numbers, categories, texts, or literally anything. If you have ever created any model , you already know that you can't use Textual Data to train ...
Continue readingMissing Value Treatment – Mean, Median, Mode, KNN Imputation, and Prediction
Missing Value treatment is no doubt one of the most important parts of the whole process of building a model. Why?Because we can't afford to eliminate rows wherever there is a missing value in any of the columns. ...
Continue readingStory of Bias, Variance, Bias-Variance Trade-Off
TheDataMonk
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Machine Learning , Statistics , Uncategorized
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Why do we predict?We predict in order to identify the trend of the future by using our sample data set. Whenever we create a model, we try to create a formula out of our sample data set. And ...
Continue readingMulticollinearity in Simple Terms
TheDataMonk
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Machine Learning , Statistics , Uncategorized
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We all know the definition of multi-collinearity i.e. when 2 or more explanatory variable in multi regression model are highly linearly related then it's called multicollinearityExample - Age and Selling price of a CarEducation and Annual IncomeHeight and ...
Continue readingGRE Verbal | Barron’s 800 Destroyed | Day 10
We are already good with 220 words, lets's pass that 250 mark. All the words given below are directly from Barron's 800 most frequent words. 251. abeyance - temporary suspensionIf you have ever created an ...
Continue reading5 Most Important SQL questions for your Data Science Interview
SQL is the bread and butter of an analyst. You can't survive in the Data Science industry with a grip on this 'easy-looking' query language. I have been interviewed for more than 30 companies in the past 3-4 ...
Continue readingCross Validation and varImp in R
TheDataMonk
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Machine Learning , Statistics , Uncategorized
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I was onto our next book - Linear,Ridge, LAASO, and Elastic Net Algorithm explained in layman terms with code in R , when we thought of covering the simple concepts which are quite helpful while creating models.Cross Validation ...
Continue readingRidge vs LASSO vs Elastic Net Regression
TheDataMonk
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Machine Learning , Statistics , Uncategorized
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Ridge and LASSO are two important regression models which comes handy when Linear Regression fails to work.This topic needed a different mention without it's important to understand COST function and the way it's calculated for Ridge,LASSO, and any ...
Continue readingLinear, LASSO, Elastic Net, and Ridge Regression in Layman terms (R) with complete code – Part 1
TheDataMonk
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Machine Learning , Statistics , Uncategorized
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Linear, LASSO, Elastic Net, and Ridge Regression are the four regression techniques which are helpful to predict or extrapolate the prediction using the historic data. Linear doesn't have any inclination towards the value of lambda.LASSO ...
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