Programming

From https://iamtrask.github.io/2015/07/12/basic-python-network/ import numpy as np sigmoid function def nonlin(x,deriv=False): if(deriv==True): return x*(1-x) return 1/(1+np.exp(-x)) input dataset X = np.array([ [0,0,1], [0,1,1], [1,0,1], [1,1,1] ]) output dataset y = np.array([[0,0,1,1]]).T seed random numbers to make calculation deterministic (just a good practice) np.random.seed(1) initialize weights randomly with mean 0 syn0 = 2*np.random.random((3,1)) - 1 print(syn0) ## [[-0.16595599] ## [ 0.44064899] ## [-0.99977125]] variables l0 is input layer l1 is hidden layer l1_error is the loss function l1_delta is the gradient descent function for calculating the back-propagation syn0 are synapses, weights between l0 and l1, and also how the weights are updated are shown. [Read More]

You’re getting ready to staff the clinic for March this year. You want to know how many visits took place in March last year, to help you prepare. Write a command that will produce a Series made up of the March data from df from all four clinic sites and save it to the variable march. #import /;../,codecademylib3 import pandas as pd df = pd.DataFrame([ ['January', 100, 100, 23, 100], ['February', 51, 45, 145, 45], ['March', 81, 96, 65, 96], ['April', 80, 80, 54, 180], ['May', 51, 54, 54, 154], ['June', 112, 109, 79, 129]], columns=['month', 'clinic_east', 'clinic_north', 'clinic_south', 'clinic_west']) print(df) ## month clinic_east clinic_north clinic_south clinic_west ## 0 January 100 100 23 100 ## 1 February 51 45 145 45 ## 2 March 81 96 65 96 ## 3 April 80 80 54 180 ## 4 May 51 54 54 154 ## 5 June 112 109 79 129 # integer location within dataframe # locations are zero indexed and doesn't include the ending integer march = df. [Read More]

• Version Control and GitHub + Main/Branches, Push/Pull/Merge
• Functions/Modules
  • Methods should be deep.
  • Write the interface first
• Try to minimize exceptions
  • define them away
• Be strategic + Invest in building the future/don’t introduce bad code today
• Write the unit test before the useful code
• Make sure you do input validation