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Updated 4 years ago
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.