Data Science Jupyter Notebooks
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Explore the world of Data Science through Jupyter Notebooks—insights, tutorials, and tools to boost your data journey. Code, analyze, and visualize smarter with every post.
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In Python, building AI-powered Telegram bots unlocks massive potential for image generation, processing, and automation—master this to create viral tools and ace full-stack interviews! 🤖

# Basic Bot Setup - The foundation (PTB v20+ Async)
from telegram.ext import Application, CommandHandler, MessageHandler, filters

async def start(update, context):
await update.message.reply_text(
" AI Image Bot Active!\n"
"/generate - Create images from text\n"
"/enhance - Improve photo quality\n"
"/help - Full command list"
)

app = Application.builder().token("YOUR_BOT_TOKEN").build()
app.add_handler(CommandHandler("start", start))
app.run_polling()


# Image Generation - DALL-E Integration (OpenAI)
import openai
from telegram.ext import ContextTypes

openai.api_key = os.getenv("OPENAI_API_KEY")

async def generate(update: Update, context: ContextTypes.DEFAULT_TYPE):
if not context.args:
await update.message.reply_text(" Usage: /generate cute robot astronaut")
return

prompt = " ".join(context.args)
try:
response = openai.Image.create(
prompt=prompt,
n=1,
size="1024x1024"
)
await update.message.reply_photo(
photo=response['data'][0]['url'],
caption=f"🎨 Generated: *{prompt}*",
parse_mode="Markdown"
)
except Exception as e:
await update.message.reply_text(f"🔥 Error: {str(e)}")

app.add_handler(CommandHandler("generate", generate))


Learn more: https://hackmd.io/@husseinsheikho/building-AI-powered-Telegram-bots

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https://t.iss.one/DataScienceM 🦾
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