|Coursera Deep Learning MOOC by Andrew Ng Convolutional Neural Net|
Sunday, November 12, 2017
Matrix Vector Representation of an Image - Image Classification for Machine Learning
Each pixel intensity can be represented with RGB values - red green blue. See this Coursera Deep Learning MOOC by Andrew Ng. The RGB data of an image is known as the three 3 channels. Each is a matrix. We vectorize the RGB data into feature matrix X. Dimension length of X is = width_pixel multiply by height_pixel multiply by number of channels 3. E.g. the digits in LSMNT are 28 by 28 by 1 because they are black and white, so instead of 3 channels, it only has one channel.
import cv2 cv2.imread() cv2.resize() .tranpose() on arrays .reshape() on arrays
This review is updated continuously throughout the program. Yay I just joined the Udacity Nanodegree for Digital Marketing! I am such an Uda...
In this downtown startup work space design the designers used fat boy bean bags and an extra wide step tiered staircase to create work space...
Can hack schools solve Silicon Valley's talent crunch? The truth about coding bootcamps and the students left behind http://t.co/xXNfqN...