- numerical-utilities VS clml
- numerical-utilities VS ultralisp
- numerical-utilities VS data-frame
- numerical-utilities VS mgl
- numerical-utilities VS plot
- numerical-utilities VS incanter
- numerical-utilities VS cl-statistics
- numerical-utilities VS mgl-mat
- numerical-utilities VS Petalisp
- numerical-utilities VS awesome-cl
Numerical-utilities Alternatives
Similar projects and alternatives to numerical-utilities
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cheatsheets
Posit Cheat Sheets - Can also be found at https://posit.co/resources/cheatsheets/. (by rstudio)
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
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mgl-mat
MAT is library for working with multi-dimensional arrays which supports efficient interfacing to foreign and CUDA code. BLAS and CUBLAS bindings are available.
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better numerical-utilities alternative or higher similarity.
numerical-utilities reviews and mentions
Posts with mentions or reviews of numerical-utilities.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-07-23.
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Uncle Stats Wants You
Refresh the histogram code. Tamas Papp has a lot of good code that needs dusting off. The histogram code has a some bitrot that can be easily cleaned up and would make a nice addition. See the bottom of the statistics.lisp file.
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New Lisp-Stat Release
I think this depends on what part of the statistics universe you're working in.
For example, within Lisp-Stat the statistics routines [1] were written by an econometrician working for the Austrian government (Julia folks might know him - Tamas Papp). It would not be exaggerating to say his job depending on it. These are state of the art, high performance algorithms, equal to anything available in R or Python. So, if you're doing econometrics, or something related, everything you need is already there in the tin.
For machine learning, there's CLML [2], developed by NTT. This is the largest telco in Japan, equivalent to ATT in the USA. As well, there is MGL [3], used to win the Higgs Boson challenge a few years back. Both actively maintained.
For linear algebra, MagicCL was mention elsewhere in the thread. My favourite is MGL-MAT [4], also by the author of MGL. This supports both BLAS and CUBLAS (CUDA for GPUs) for solutions.
Finally, there's the XLISP-STAT archive [5]. Prior to Luke Tierney, the author of XLISP-Stat joining the core R team, XLISP-STAT was the dominate statistical computing platform. There's heaps of stuff in the archive, most at least as good as what's in base R, that could be ported to Lisp-Stat.
Common Lisp is a viable platform for statistics and machine learning. It isn't (yet) quite as well organised as R or Python, but it's all there.
[1] https://github.com/Lisp-Stat/numerical-utilities/blob/master...
Stats
Basic numerical-utilities repo stats
2
13
5.5
4 months ago
Lisp-Stat/numerical-utilities is an open source project licensed under Microsoft Public License which is an OSI approved license.
The primary programming language of numerical-utilities is Common Lisp.
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