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/* The solution found here: http://www.aspsnippets.com/Articles/Change-URL-in-Browser-Address-Bar-without-reloading-using-JavaScript-and-jQuery.aspx */ | |
/** HTML5 History pushState method | |
* The pushState method works similar to window.location but it does not refresh or reload the page and it will modify the URL even if the page does not exists. The pushState method actually inserts an entry into the history of the browsers which allows us to go back and forth using the browser’s forward and back buttons. | |
* The pushState method accepts the following three parameters. | |
* 1. State object: - The state object is a JavaScript object which can contain any details about the page and must be serializable. | |
* 2. Title: - The title of the page. | |
* 3. URL – The URL of the page. | |
*/ |
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import speech_recognition as sr | |
import pyttsx3 | |
import openai | |
openai.api_key = "Your API Key" | |
engine = pyttsx3.init() | |
voices = engine.getProperty('voices') | |
engine.setProperty('voices', voices[1].id) |
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<template> | |
<div class="ui cards" style="margin: 10px"> | |
<div class="ui icon input" style="width: 100%"> | |
<input type="text" placeholder="Search..." v-model="searchQuery" /> | |
<i class="search icon"></i> | |
</div> | |
<div | |
class="card ui fluid" | |
v-for="product in searchedProducts" | |
:key="product.id" |
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/* | |
Google Drive API: | |
Demonstration to: | |
1. upload | |
2. delete | |
3. create public URL of a file. | |
required npm package: googleapis | |
*/ | |
const { google } = require('googleapis'); |
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@rem Create by Erik van Oost for version PC/LR 12.55 | |
@if not exist C:\temp mkdir C:\temp | |
@echo %~f0 | |
@set scriptpath=%~f0\..\ | |
@echo Extracting setup files with 7Zip | |
%scriptpath%7z.exe x %scriptpath%SetupVugen.exe -oC:\temp\SetupVugen -y | |
%scriptpath%7z.exe x %scriptpath%SetupAnalysis.exe -oC:\temp\SetupAnalysis -y | |
@echo Installing prerequisites for Vugen |
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from numpy import exp, array, random, dot | |
training_set_inputs = array([[0, 0, 1], [1, 1, 1], [1, 0, 1], [0, 1, 1]]) | |
training_set_outputs = array([[0, 1, 1, 0]]).T | |
random.seed(1) | |
synaptic_weights = 2 * random.random((3, 1)) - 1 | |
for iteration in xrange(10000): | |
output = 1 / (1 + exp(-(dot(training_set_inputs, synaptic_weights)))) | |
synaptic_weights += dot(training_set_inputs.T, (training_set_outputs - output) * output * (1 - output)) | |
print 1 / (1 + exp(-(dot(array([1, 0, 0]), synaptic_weights)))) |
A complete list of books, articles, blog posts, videos and neat pages that support Data Fundamentals (H), organised by Unit.
If the resource is available online (legally) I have included a link to it. Each entry has symbols following it.
- ⨕⨕⨕ indicates difficulty/depth, from ⨕ (easy to pick up intro, no background required) through ⨕⨕⨕⨕⨕ (graduate level textbook, maths heavy, expect equations)
- ⭐ indicates a particularly recommended resource; 🌟 is a very strongly recommended resource and you should look at it.
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