Adarsha Regmi

categorical data

Data types for categorical data.

Some useful methods in R that helps while working with the similar type of data

a) factor

multiple values are considered as categories and neglicted duplicate values

eg;

 survey_vector <- c(“M”, “F”, “F”, “M”, “M”)factor_survey_vector <- factor(survey_vector)

b) levels

placing label for the categories

levels(factor_survey_vector) <-c("Female","Male")factor_survey_vector

c) summary

similar to the way there exist summary method in pandas in python here we’ve summary method

summary(my_var)

that’s all for now. Keep learning.

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cont.

Similar to numpy where exist multi-dimensional array, the pytorch tensorflow are build up of tensors.

TENSORS

ever heard of it. Let’s begin.

  • They are same as numpy arrays except that they have flexibility to run in GPU.

Types of

  1. FloatTensor: 32-bit float
  2. DoubleTensor: 64-bit float
  3. HalfTensor: 16-bit float
  4. IntTensor: 32-bit int
  5. LongTensor: 64-bit int
tensor vs nd array

some basic functions

  • torch.add()
  • torch.sub()
  • torch.mm() <matrix multiplication>
  • torch.div()
  • torch.t()
  • torch.cat()
  • a.reshape()

# converting the numpy array to tensor

  • tensor = torch.from_numpy(a)

In next section lets discuss more about the common pytorch Modules… part 3 .

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