  We study individual pulses of Vela (PSR\ B0833-45\,/\,J0835-4510) from daily
observations of over three hours (around 120,000 pulses per observation),
performed simultaneously with the two radio telescopes at the Argentine
Institute of Radioastronomy. We select 4 days of observations in January-March
2021 and study their statistical properties with machine learning techniques.
We first use density based DBSCAN clustering techniques, associating pulses
mainly by amplitudes, and find a correlation between higher amplitudes and
earlier arrival times. We also find a weaker (polarization dependent)
correlation with the mean width of the pulses. We identify clusters of the
so-called mini-giant pulses, with $\sim10\times$ the average pulse amplitude.
We then perform an independent study, with Self-Organizing Maps (SOM)
clustering techniques. We use Variational AutoEncoder (VAE) reconstruction of
the pulses to separate them clearly from the noise and select one of the days
of observation to train VAE and apply it to thre rest of the observations. We
use SOM to determine 4 clusters of pulses per day per radio telescope and
conclude that our main results are robust and self-consistent. These results
support models for emitting regions at different heights (separated each by
roughly a hundred km) in the pulsar magnetosphere. We also model the pulses
amplitude distribution with interstellar scintillation patterns at the
inter-pulses time-scale finding a characterizing exponent
$n_{\mathrm{ISS}}\sim7-10$. In the appendices we discuss independent checks of
hardware systematics with the simultaneous use of the two radio telescopes in
different one-polarization / two-polarizations configurations. We also provide
a detailed analysis of the processes of radio-interferences cleaning and
individual pulse folding.
