reicolina

The following Javascript method takes a query parameter and the URL it belongs too, and it returns the value associated with that query parameter.

function getQueryStringValue(param, url) {
  if (!url) {
      // handle null or undefined
  	return null;
  }
  var regex = new RegExp("[?&]" + param + "(=([^&#]*)|&|#|$)");
  var results = regex.exec(url);

reicolina

#     \\Y|M|
#     ~~..'~
#     (  \ )
#      \ =/
#      _\/_
#     /    -_
#    <       \
#     \^-_-^\ \   iii
#     <\v =======uu==>
# SR&ED DATA GENERATOR

reicolina

#  ___             ,_,              ___
# (o,o)           (o,o)         ,,,(o,o),,,
# {`"'}           {`"'}          ';:`-':;'
# -"-"-           -"-"-            -"-"-
#
# AMPLIFY FOR SELLING: CONTACT IMPORT SCRIPT
# ==========================================
# 1.- Obtain CSV file(s) from your data source.
# 2.- Save the CSV file in the same folder as this script.
# 3.- Replace the HOOTSUITE_MEMBER_ID, AMPLIFY_API_KEY, CRM_MAPPING_URL

reicolina

Machine Learning Reference Material Guide

Math Theory

Linear Argebra:

In ML, Linear Algebra comes up everywhere. Topics such as Principal Component Analysis (PCA), Singular Value Decomposition (SVD), Eigendecomposition of a matrix, LU Decomposition, QR Decomposition/Factorization, Symmetric Matrices, Orthogonalization & Orthonormalization, Matrix Operations, Projections, Eigenvalues & Eigenvectors, Vector Spaces and Norms are needed for understanding the optimization methods used for machine learning.

• Deep Learning Book, Chapter 2: Linear Algebra. A quick review of the linear algebra concepts relevant to machine learning. https://goo.gl/O5vgpm
• A First Course in Linear Model Theory by Nalini Ravishanker and Dipak Dey. Textbook introducing linear algebra in a statistical context. https://goo.gl/2A4Wi5

Probability Theory and Statistics: