Machine Learning Course 9 Study Log (Advice for Applying Machine Learning)

(1) Complexity of Models

(2) Regularization

(3) Data Size

(4)

(5)

(6)

(7)

(8)

(9) Rare Class

(10) Two Measurements

Enable QGIS on a brower

1: qgis2leaf

webmap creation in open source GIS QGIS

2: Apache
https://www.youtube.com/watch?v=17qhikHv5hY

3: Leaflet

http://leafletjs.com/examples.html#leaflet-tutorials

What does a Product Manager Do?

"What does a Product Manager Do?"

My own understanding is that a Product Manager's job includes:
0) Product's Core Value and Competition
1) Product Architecture
2) Product Life Cycle or Time Table (and management)
3) Communication
4) Also, in my position, I need to code all algorithms and data I designed

Then, I searched the website on the topic, and get something:
From: http://www.smashingmagazine.com/2014/09/17/why-companies-need-full-time-product-managers/

With that as the backdrop, my definition of the role of a product manager would be to achieve business success by meeting user needs through the continual planning and execution of digital product solutions.

...

Marty Cagan has a great list of common tasks that product managers are responsible for in his ebook Behind Every Great Product (PDF). The tasks include:

1. identifying and assessing the validity and feasibility of product opportunities,
2. making sure the right product is delivered at the right time,
3. developing a product strategy and road map for development,
4. leading the team in executing the product’s road map,
5. evangelizing the product internally to the executive team and colleagues,
6. representing customers through the product development process.

Machine Learning Course 8 Study Log (Neural Network II)

(1)

(2)

(3)

(4) The Back proragation Algorithm

(5)

(6)

(7) Verify Gradient Calculation

(8)

(9)

(10)

(11) Problem of 0 as starting points

(12)

(13) All-In-One

(14) All-In-One

Machine Learning Course 5 Study Log (Matlab)

1:
A = 1;
A == 1;
A = B;
1 && 0
xor(0, 1)
b = 'hi';
c = ( 3 > 1);
disp(sprinf('%0.2f',a));
format short/long
A = [2 3; 4 5];
A = [0:0.1:1];
A = ones(2,3);
A = zeros(2,3);
A = rand(2,3); %uniform
A = randn(2,3); %normally distributed random numbers
A = eye(2,3); %identity matrix

2:
size()
length()
pwd
ls
load or importdata
who or whos
clear
A = B(1:2)
A = B(1:2,:)
A(:,2)
A(:,[1 2])
A(:,[1:1:3])
A(1:2,:) = [1; 2]
C = [A; B]
C = [A B] or [A, B]
save 'text.txt' A - ascii
save 'text.mat' A %binary format

3:
log(A) or abs(A)
A + 2
A * 2 or A .* 2
-A
A * B
A .* B
(A)'
pinv(A)
A < 3
find(A < 3)
sum(sum(A))
prod(A)
floor , ceil
max(rand(3), rand(3))
max(A, [], 1)
A(:)
flipud

4:
plot()
plot(x,y,'r')
hold on;
xlabel
ylabel
legend
title
print -dpng 'test.png'
figure(1) %define which figure to use
subplot(1, 2, 1) % cut the plot into 1 * 2 and then use 1
imagesc, colorbar, colormap gray

5:
for i in 1:0.1:10
  XXX
end

break;
continue;

while i < 10
  XXX
end

if
elseif
elseif
else
end

function [y1, y2] = a_function_name(x)
   y1 = x^2
   y2 = x^3


search path; addpath ('')

6:

7.

Machine Learning Course 8 Study Log (Neural Network)

(1)

(2)

(3)

(4)

The Idea under Neural Network is to Learn Required Composed Features As it Wants

(5)

(6)

(7)

(8)

Machine Learning Course 7 Study Log (Regularization)

(1)

(2)

(3)

(4)