clusters
Variety of clustering tools for the Common Lisp (by sirherrbatka)
numcl-benchmarks
benchmarks against numpy, julia (by numcl)
clusters | numcl-benchmarks | |
---|---|---|
1 | 1 | |
5 | 4 | |
- | - | |
0.0 | 0.0 | |
about 2 years ago | almost 4 years ago | |
Common Lisp | Python | |
BSD 2-clause "Simplified" License | GNU General Public License v3.0 or later |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
clusters
Posts with mentions or reviews of clusters.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-07-16.
-
Anybody using Common Lisp or clojure for data science
Yeah, I use CL for data science, despite lack of suitable tools. I even ended up writing my own: https://github.com/sirherrbatka/clusters https://github.com/sirherrbatka/vellum https://github.com/sirherrbatka/vellum-plot https://github.com/sirherrbatka/statistical-learning
numcl-benchmarks
Posts with mentions or reviews of numcl-benchmarks.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-07-16.
-
Anybody using Common Lisp or clojure for data science
For example, numcl aims to be a clone of numpy. The published benchmarks are not impressive. My aim is not to second guess the author or belittle his project and effort.
What are some alternatives?
When comparing clusters and numcl-benchmarks you can also consider the following projects:
vellum-plot
neanderthal - Fast Clojure Matrix Library
qvm - The high-performance and featureful Quil simulator.
vellum - Data Frames for Common Lisp
quilc - The optimizing Quil compiler.
dtype-next - A Clojure library designed to aid in the implementation of high performance algorithms and systems.
CLPython - An implementation of Python in Common Lisp
statistical-learning - Statistical learning models for the Common Lisp
clusters vs vellum-plot
numcl-benchmarks vs neanderthal
clusters vs qvm
numcl-benchmarks vs vellum
clusters vs quilc
numcl-benchmarks vs qvm
clusters vs dtype-next
numcl-benchmarks vs vellum-plot
clusters vs neanderthal
numcl-benchmarks vs CLPython
clusters vs vellum
numcl-benchmarks vs statistical-learning