Skip to content

Instantly share code, notes, and snippets.

View maasencioh's full-sized avatar

Miguel Angel Asencio Hurtado maasencioh

View GitHub Profile
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
@maasencioh
maasencioh / ml-assign1-maasencioh.ipynb
Created September 9, 2015 03:15
First machine learning assignment
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
@maasencioh
maasencioh / datalog.txt
Created February 7, 2016 00:53
data example from solmaforo
Sede 2
T:22.3H:45%UV:1
C|01.07.2015|17:05:39
T:22.2H:46%UV:1
C|01.07.2015|17:11:05
T:22.2H:46%UV:1
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.

Keybase proof

I hereby claim:

  • I am maasencioh on github.
  • I am maasencioh (https://keybase.io/maasencioh) on keybase.
  • I have a public key ASDaTArJ4TlWZIczHrs__rp6nqlUORqIzN2Rel_AvmumEQo

To claim this, I am signing this object:

var SLR = ML.Regression.SLR;
var inputs = [10, 20, 50, 75, 80];
var outputs = [30, 50, 80, 100, 130];
var regression = new SLR(inputs, outputs);
var y = regression.predict(85);
var min = 1000000;
var max = -100000;

Installing JS into a Huzzah ESP8266 and run a Telegram bot in there

Installing Espruino

The first thing that will be needed is the drivers, so you will need to run:

$ pip install pyserial
$ pip2 install esptool
@maasencioh
maasencioh / levmarq.c
Created August 18, 2016 15:51 — forked from rbabich/ levmarq - Levenberg-Marquardt in plain C
A simple implementation of the Levenberg-Marquardt algorithm in plain C
/*
* levmarq.c
*
* This file contains an implementation of the Levenberg-Marquardt algorithm
* for solving least-squares problems, together with some supporting routines
* for Cholesky decomposition and inversion. No attempt has been made at
* optimization. In particular, memory use in the matrix routines could be
* cut in half with a little effort (and some loss of clarity).
*
* It is assumed that the compiler supports variable-length arrays as