Status

Currently INACTIVE as this is part of my linalg.rs project.

-- @japaric, 2016-05-02

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linalg examples

The main goal of these examples is to showcase linalg API. A secondary goal is to compare the ergonomics of doing numerical computing in Rust vs in other languages, to this extend implementations of each example are provided in other languages. And, as this library currently lacks (multi-language) benchmarks, some non-scientific measurements are included (I mainly wanted to check that linalg is not slower than NumPy).

Examples included:

• classifier: Multiclass classification using logistic regression and the one vs all strategy
• descent: Multivariate linear regression using the iterative gradient descent algorithm
• nn: Neural network that recognizes hand written digits
• normal: Multivariate linear regression using the normal equation

Each example is a cargo project.

Meta

Information about the system where the measurements were performed

Python

$ python -V
Python 2.7.9

Kernel

Linux ideapad 4.0.1 #1 SMP PREEMPT Wed Apr 29 13:47:28 PET 2015 x86_64 GNU/Linux

CPU

Architecture:          x86_64
CPU op-mode(s):        32-bit, 64-bit
Byte Order:            Little Endian
CPU(s):                8
On-line CPU(s) list:   0-7
Thread(s) per core:    2
Core(s) per socket:    4
Socket(s):             1
NUMA node(s):          1
Vendor ID:             GenuineIntel
CPU family:            6
Model:                 60
Model name:            Intel(R) Core(TM) i7-4702MQ CPU @ 2.20GHz
Stepping:              3
CPU MHz:               801.453
CPU max MHz:           3200.0000
CPU min MHz:           800.0000
BogoMIPS:              4389.99
Virtualization:        VT-x
L1d cache:             32K
L1i cache:             32K
L2 cache:              256K
L3 cache:              6144K
NUMA node0 CPU(s):     0-7

License

These examples are dual licensed under the Apache 2.0 license and the MIT license.

See LICENSE-APACHE and LICENSE-MIT for more details.