graph LR
A[Tensorflow] --implements--> B[Deep neural nets]
A --was developed by --> C[Google]
graph LR
graph LR
A[Tensorflow] --implements--> B[Deep neural nets]
A --was developed by --> C[Google]
graph LR
graph LR
A((Keras 3)) --is a high level API for --> B((Tensorflow))
B --was developed by-->H[Google]
C((Pytorch)) --was developed by-->D[Meta]
A --is a high level API for --> C
A --is a high level API for --> F[JAX]
F --was developed by-->H
A --implements--> G[Deep neural nets]
B --implements--> G
import numpy as np | |
import scipy.stats as stats | |
# Number of trials and successes for each group | |
n_1 = 100 | |
x_1 = 6 | |
n_2 = 125 | |
x_2 = 5 | |
# Parameters for the prior distributions |
#Test imports | |
import urllib2, ssl, json, time, re | |
from bs4 import BeautifulSoup | |
from selenium import webdriver | |
from selenium.webdriver.support.ui import Select | |
#Test urllib2 | |
import urllib2 | |
response = urllib2.urlopen('https://en.wikipedia.org/wiki/Test', context=ssl.SSLContext(ssl.PROTOCOL_TLSv1)) |
<head> | |
<script src="http://cdn.leafletjs.com/leaflet/v0.7.7/leaflet.js"></script> | |
<script src="https://cdnjs.cloudflare.com/ajax/libs/d3/4.2.1/d3.min.js"></script> | |
<link rel="stylesheet" href="http://cdn.leafletjs.com/leaflet/v0.7.7/leaflet.css"/> | |
<script src="https://cdnjs.cloudflare.com/ajax/libs/d3/3.5.16/d3.min.js"></script> | |
<style> #mapid { | |
height: 800px; | |
} </style> | |
</head> | |
<body> |