Friday, January 20, 2017

Machine Learning code pattern 01

Code pattern 01 numpy use array().T to get matrix transpose


X = [1,2,3]
XT = array(X).T

Machine Learning Concepts 01

 There are three main machine learning styles:

  1.  Supervised learning 
  2.  Unsupervised learning
  3.  Reninforcement learning

Wednesday, January 18, 2017

Udacity Machine learning Nanodegree Syllabus and Summary

udacity nanodegree - becoming a machine learning engineer. This is my personal notes summarizing what I learned from the section, consider it my personal study notes. The part I labeled syllabus is the actual outline of the course (e.g. I try to use section title as the syllabus section title)

Section supervised learning
Sub section artificial neutral networks
Sub section neural networks
     how does a neuron work (illustrated)
     How artificial neural network works (illustrated) perceptron
     A group of inputs, each with a weights, processed by the network and output 1 of and only if a preconfigured threshold is met
     Artificial neural networks can be tuned

  • Think of inputs as signals with different strengths, weights as sensitivity to those strengths. Can be tuned and adjusted to computer variety of tasks. Hence a collection of perceptroncomputing units is powerful
  • The weights sum of all the inputs is called the activation
  • When activation is greater than the threshold theta the perceptron outputs 1

Friday, January 13, 2017

Data Science for Business by Provost Fawcett data science book review

  • Interesting business approach to understand and apply data science
  • Use verbose texts when explaining simple concepts
  • Introduce advanced concepts like Information Gain and Entropy early in the book pg51. Less accessible for beginners. Good for people preparing for interviews and people who already got an introduction to machine learning
  • Writes the full formula out, avoid using sigma notation to make it more accessible for business readers
  • Useful graph of entropy pg 52
  • Helpful graphical illustration pg54-pg55 two trees with different information gain
  • The learning curve is not a slowly ascending one. The topics jump around in this book
  • Variance measures impurity pg56

Thursday, January 12, 2017

Udacity Machine Learning Nanodegree Linear Regression sample code

from sklearn import linear_model

reg = linear_model.LinearRegression()

Codecademy SQL Table Transformation Subqueries Walkthrough

  • 1. Table Transformation
    • SELECT * FROM flights WHERE (SELECT code FROM airports WHERE elevation < 2000); 
    • Nested subqueries 
    • First get all the codes from airports table if its elevation is smaller than 2000
    • Use this as a filter to query all columns of data from the flights table
    • Don't forget the ; semicolon in the end

Friday, January 6, 2017

Udacity Year in Review

Udacity online course highlighted itssuccesses and milestones in 2016. 
  • Udacity currently offers 159 courses
  • Udacity's site-wide busiest time for learning is the Month of October
  • Student watched the Developing Android Apps video by Google the most
  • Read the full article here Udacity 2016 Year in Review