What is the difference between Training dataset, Testing Dataset, Validation dataset? What is the Common Ratio?
Training Dataset The sample of data used to fit the model.The actual dataset that we use to train the model. The
How to deal with imbalanced dataset in Machine Learning?
There are 5 different methods for dealing with imbalanced datasets:Change the performance metric Change the algorithm Over sample minority
Explain in detail about Normalization and Standardization?
Standardization Standardization is the process of rescaling the features so that they’ll have the properties of a Gaussian distribution withμ=0 and
What is Feature Scaling?
Feature Scaling or Standardization: It is a step of Data Preprocessing which is applied to independent variables or features of
What do you mean by Binning in Machine Learning? What are the differences between Fixed width binning and Adoptive binning?
Data binning, bucketing is a data pre-processing method used to minimize the effects of observation errors. Binning is the process of transforming
Army to Use AI to Boost Combat Capabilities in the next 2-3 years
Do you know in next couple of years the Indian Army is likely to start using Artificial Intelligence with an
What is the importance of Mean, Variance, Standard Deviation in identifying details of particular feature in Dataset? How do you calculate it?
Mean is average of a given set of data.Variance is the sum of squares of differences between all numbers and means.Standard Deviation is
What do you mean by Dummy Variable? Where it is used in Machine Learning?
If there are n number of categories in categorical attribute, n new attributes will be created. These attributes created are called Dummy Variables. These dummy
What are the differences between Mean, Median, Mode? How these are helpful to deal with the missing values in the given dataset?
MeanMean is the average of the Dataset. It is the ratio of Sum of total observations to the Total number
What do you mean by Imputer?
Imputation is the process of replacing missing data with substituted values. It substitutes missing values by the mean or median of the remaining