👷♀️🚧🚧🚧👷 To strangers: this is a DRAFT. Don't do the same things as me!
Dependencies:
- Python 2.7 / 3.6
- Open Babel with Python Binding
- Officially recommended: Compile with Python Binding option enabled
- Compiling Open Babel (Latest Release: GitHub)
# Use the native inference API to send a text message to Anthropic Claude. | |
import boto3 | |
import json | |
import base64 | |
import httpx | |
from botocore.exceptions import ClientError | |
# Create a Bedrock Runtime client in the AWS Region of your choice. |
<html> | |
<head> | |
<title>Hls.js demo - basic usage</title> | |
</head> | |
<body> | |
<script src="https://cdn.jsdelivr.net/npm/hls.js@1.5.1/dist/hls.min.js"></script> | |
<center> | |
<h1>Hls.js demo - basic usage</h1> | |
<video height="600" id="video" controls="" disableremoteplayback=""><source type="video/mp4"></video> |
gist_id="YOUR_GIST_ID" # Replace with the actual Gist ID | |
download_path="." # Specify the download directory (optional) | |
# Get Gist information as JSON | |
gist_info=$(curl -s "https://api.github.com/gists/$gist_id") | |
# Extract file URLs using jq | |
file_urls=$(echo "$gist_info" | jq -r '.files[].raw_url') |
I keep losing my keys. How can I keep track of them? |
👷♀️🚧🚧🚧👷 To strangers: this is a DRAFT. Don't do the same things as me!
Dependencies:
Revision list for Qwiklabs Challenge Labs: Classify Text into Categories with the Natural Language API (https://google.qwiklabs.com/focuses/12704?parent=catalog) |
Revision list for Qwiklabs Lab: Classify Text into Categories with the Natural Language API (https://google.qwiklabs.com/focuses/1749?parent=catalog) |
{ | |
"$schema": "https://raw.githubusercontent.com/jsonresume/resume-schema/v1.0.0/schema.json", | |
"basics": { | |
"name": "黃種平", | |
"label": "資料工程師 @ 台灣塑膠工業股份有限公司", | |
"picture": "", | |
"email": "purpleslovemail@gmail.com", | |
"phone": "", | |
"summary": "曾擔任 6 年以上之資料分析師及資料工程師,擅長於進行機器學習領域之資料處理、收集、建立預測模型、持續整合管線、及部署推論模型事務。能快速學習新科技並應用於地端及雲端。具有醫療領域及製造業之 MLOps 建構經驗。", | |
"location": { |
import random | |
ROUNDS = 10000 # The times to re-play | |
COUNT_CHANGE = 0 # If we change the chosen door, the times receiving the car | |
COUNT_NOT_CHANGE = 0 # If we don't change the chosen door, the times receiving the car | |
# Play the game, and choose to change the door after first picked | |
for _ in range(ROUNDS): | |
# Create 3 doors | |
doors = {0: 0, 1: 0, 2: 0} |
Creator "Mark Newman on Sat Jul 22 06:24:59 2006" | |
graph | |
[ | |
directed 0 | |
node | |
[ | |
id 0 | |
label "ABRAMSON, G" | |
] | |
node |