Twitter news topic popularity prediction using linear regression (minimal)

Dataset: https://archive.ics.uci.edu/ml/datasets/Buzz+in+social+media+

Assumptions on linear regression

A strict version of assumptions used here is explained in Gauss-Markov theorem. This theorem explains all the assumption for applying ordinary least squares (OLS). However, when we are using a generalized linear regression, the assumptions are more or less losely followed (an example can be foudn here and here).

Linearity
No perfect colinearity
Strict exogenity
Homoskedasticity
Normal error term

# Uncomment and run the commands below if imports fail
# !conda install numpy pytorch torchvision cpuonly -c pytorch -y
# !pip install matplotlib --upgrade --quiet
!pip install jovian --upgrade --quiet

!conda install numpy pytorch torchvision cpuonly -c pytorch -y

Collecting package metadata (current_repodata.json): done
Solving environment: done


==> WARNING: A newer version of conda exists. <==
  current version: 4.8.2
  latest version: 4.8.3

Please update conda by running

    $ conda update -n base conda



# All requested packages already installed.