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/* brand.css - Agentic AI Brand Identity for Web Applications */

/* Root variables for scalability and theming */
:root {
  /* Color Palette */
  --primary-color: #1a73e8; /* Bright blue - conveys innovation and trust */
  --secondary-color: #34c759; /* Vibrant green - suggests growth and AI dynamism */
  --accent-color: #fbbc05; /* Warm yellow - highlights and calls-to-action */
  --background-dark: #1f2a44; /* Dark navy - modern, tech-focused background */
  --background-light: #f5f7fa; /* Light gray - clean and minimal */

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# Open edX APIs often require an access token that is obtained through the OAuth2 protocol. Here are the general steps you would take:
# Request an access token: The first step is to request an access token. For this, you would send a POST request to the /oauth2/access_token endpoint with your client ID and secret. Here’s an example of how to do it with requests in Python:
import requests
import json

url = "https://your-open-edx-instance.com/oauth2/access_token"

headers = {
    "Content-Type": "application/json"
}

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import tensorflow as tf

# Define the input data
X = np.array([
  [10], # grade on first assessment
  [20], # grade on second assessment
  [30]  # grade on third assessment
])

# Define the target variable

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import tensorflow as tf

# Define the input data
X = np.array([
  [10], # grade on first assessment
  [20], # grade on second assessment
  [30]  # grade on third assessment
])

# Define the target variable

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import numpy as np

def linear_regression(X, y):
  # Add a column of ones to X to represent the bias term
  X = np.concatenate([np.ones((X.shape[0], 1)), X], axis=1)

  # Compute the transpose of X
  X_t = np.transpose(X)

  # Compute the dot product of X_t and X

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root@openedx:/edx/app/edxapp/edx-platform$ git tag | grep "open-release" | tail -1
open-release/ginkgo.1rc1

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version: '2'  
services:  
  nginx-proxy:
    image: jwilder/nginx-proxy
    container_name: nginx-proxy
    ports:
      - "80:80"
      - "443:443"
    volumes:
      - /var/run/docker.sock:/tmp/docker.sock:ro

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#!/usr/bin/env bash

#
# Script for installing Ansible and the edX configuration repostory
# onto a host to enable running ansible to complete configuration.
# This script can be used by Docker, Packer or any other system
# for building images that requires having ansible available.
#
# Can be run as follows:
#

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# wget $URL_OF_THIS_RAW_SCRIPT -O - | sudo bash

#############################################################################################
# Basic initial configuration of Ubuntu 12.04 on VirtualBox
# (execute after installing the relevant ISO on the VM through VirtualBox: http://releases.ubuntu.com/12.04/)
# 
#
# In order to access the VM from your host (e.g. OS X), forward the relevant ports on VirtualBox:
# Network -> Adapter 1 (NAT) -> Port Forwarding (http://stackoverflow.com/a/10532299/2708484)
#

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Barrier

Barrier.h

/*
  Barrier.h
 */

#include <mutex>
#include <condition_variable>