rel="stylesheet" href="style.css" />
05 {% endblock %}
06
07
08
09 {% for item in seq %}
10 - {{ item }}
11 {% endfor %}
12
13
14
9%
09.12.2021
of threads, use:
$ plzip -v -9 -n 32 package-list.txt
package-list.txt: 2.640:1, 37.88% ratio, 62.12% saved, 11626 in, 4404 out.
The -n 32
option tells plzip
to use 32 threads to perform the compression
9%
13.12.2018
], Weka [9], LIBSVM [10], and the deep learning frameworks Keras [11], TensorFlow [12], and DL4J [13].
Supported by the various possibilities to import, export, visualize, and manipulate data, KNIME offers
