Unleash the Power of AI in Your Projects: Build a Sentiment Analysis App with Azure Cognitive Services

Want to add intelligence to your applications?

Look no further than Azure Cognitive Services! This powerful suite offers pre-built AI functionalities that you can effortlessly integrate into your projects.

In this article, we'll embark on a journey to create a basic sentiment analysis application using Azure Cognitive Services. This application will analyze the sentiment of any text you provide, giving you a taste of how AI can revolutionize your work.

Prerequisites:

• An active Azure account. If you don't have one, sign up for a free Azure account.
• Basic understanding of Python programming.
• Your preferred IDE installed.

Step-by-Step Guide:

Step 1: Setting Up Azure Cognitive Service

1. Log into the Azure Portal.
2. Navigate to "Create a resource" > "AI + Machine Learning" > "Cognitive Services".
3. Fill in the required details and select the S0 tier (or F0 for a free trial).
4. Review and create your resource. Once deployed, note down the Endpoint and Keys from the "Keys and Endpoint" section.

Step 2: Installing the Azure AI SDK Open your terminal or command prompt and install the Azure AI Text Analytics client library for Python with pip:

pip install azure-ai-textanalytics --pre

pip install azure-ai-textanalytics --pre        

Step 3: Writing the Sentiment Analysis Code Create a new Python file in your IDE and import the necessary libraries:

from azure.ai.textanalytics import TextAnalyticsClient
from azure.core.credentials import AzureKeyCredential        

Set up the client using your obtained endpoint and key:

key = "your_cognitive_services_key"
endpoint = "your_cognitive_services_endpoint"

text_analytics_client = TextAnalyticsClient(endpoint=endpoint, credential=AzureKeyCredential(key))        

Design a function to perform sentiment analysis:

def analyze_sentiment(text_input):
    response = text_analytics_client.analyze_sentiment(documents=[text_input])[0]
    print("Document Sentiment: {}".format(response.sentiment))
    print("Overall scores: positive={0:.2f}; neutral={1:.2f}; negative={2:.2f} \n".format(
        response.confidence_scores.positive,
        response.confidence_scores.neutral,
        response.confidence_scores.negative,
    ))        

Step 4:Test Your AI Creation!

Put your application to the test with some sample text:

text_input = "Hey Shaghik! Azure Cognitive Services makes it easy to integrate AI into your applications."
analyze_sentiment(text_input)        

Run your Python script. You should see the sentiment analysis results printed to the console, indicating whether the sentiment is positive, neutral, or negative, along with the confidence scores.

Congratulations! You've successfully built and executed your first AI application with Azure Cognitive Services. This is just the beginning!

Expand Your Horizons:

• Explore other Azure Cognitive Services like Computer Vision and Speech Services.
• Experiment by combining multiple services for a more comprehensive application.
• Delve into building advanced models using Azure Machine Learning.

Remember, the key to mastering Azure AI is exploration and practice. Don't hesitate to dive deeper into the resources and tutorials offered by Microsoft.

Happy coding, and happy innovating with Mathematics!