AI — APIs

Popular AI APIs

API	Provider	Use Case
OpenAI	OpenAI	Text, images
Google AI	Google	Various
AWS AI	Amazon	Various
Azure AI	Microsoft	Various

OpenAI API

from openai import OpenAI

client = OpenAI(api_key="your-key")
response = client.chat.completions.create(
    model="gpt-3.5-turbo",
    messages=[{"role": "user", "content": "Hello!"}]
)

Google Cloud AI

from google.cloud import vision

client = vision.ImageAnnotatorClient()
image = vision.Image(content=content)
response = client.label_detection(image=image)

AWS AI

import boto3

comprehend = boto3.client('comprehend')
response = comprehend.detect_sentiment(
    Text='I love this!',
    LanguageCode='en'
)

Mini Practice

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Continue with Model Deployment — deploying models.

Frequently Asked Questions about APIs

What is APIs in AI?

APIs is a fundamental concept in AI. This lesson explains it step by step with clear examples, making it easy for beginners to understand.

How do I learn APIs?

Start by reading the explanation above, then try the code examples. Practice by modifying the examples and experimenting with different values. Hands-on practice is the best way to learn APIs.

Why is APIs important in AI?

APIs is essential for AI development. Understanding this concept will help you write better code and solve real-world problems more effectively.