Articles on: Tutorials

How to Create an AI service for Sentiment Analysis (Text Data)

How to Create an AI service for Sentiment Analysis:

1. Login

Make sure to visit:
Then log in to the platform with user and password

Contact us for a demo account if you don’t have a user yet

2. Dashboard

Home page shows all the experiments that you have created.
You can filter by experiment type (image, text, audio) and search

3. Create experiment I

To create the new experiment, you have to click in the "Create new experiment" button and then select the experiment type.

4. Create experiment II

Once you've selected the type of experiment, choose the task you need your model to develop.

E.g: Text Classification or Knowledge Base for Q&A

5. Create experiment III

Then you define a name and description for your experiment. Optionally, you can upload a image (E.g. company logo) for your experiment.

6. Create experiment IV

Now, it’s time to upload the data (images) that will be used to teach the platform the main patterns about the problem you want to solve:

Just drag & drop a zip file with the images organized into folders (if you had more categories in your use case then just create one folder per category).

7. Create experiment V

Optionally, you can upload a second zip file containing specific texts for validating the trained models. If not provided, the platform will separate automatically some of the texts for this goal.

8. Create experiment VI

In the last step, if you are an expert user, you can optionally modify the default experiment’s configuration. If the default configuration is used, the platform will use the best candidate models for your experiment type.

9. Experiment page I

Congrats! You have completed all the required steps to create the experiment: you have defined your problem and provided the data. You’ve finished! just shortly wait until the platform finds the best solution (model) for your problem!

10. Experiment page II

If you want, you can go to the Dataset tab, and see some stats about your data. We keep your dataset for 30 days in case you want to do changes and upload a new version (this could be helpful in case the results are not good)

11. Email notification

Once the experiment is finished and the platform have found a good solution for your problem you will receive a notification in your mailbox with a basic summary of the results and a link to the experiment page.

12. The experiment is done, your model is ready!

Once the experiment is finished, in the experiment page, you will find the best model that the platform have built for your problem

You can test it directly in the browser by clicking the “Use this model” button.

You also can see other trained models by clicking the “Try another model” button.

And that’s all! you have a ready to use service for recognizing whether a restaurant review is positive or negative with 97% accuracy!

13. Test the model page

In the test model page you can write any text you want to evaluate and get model’s result immediately. And last but not least! you can get the required code to** integrate the model** to your project or app!

14. Predict API docs - OpenAPI

If you want to, you can click in the “See the OpenAPI (formerly Swagger) specification for more details” and explore all the details related to the RESTFul API for getting model’s predictions.

15. Let's recap

In this quick introduction to our AI-Toolkit you have learned:

How to use the AI-Toolkit for Sentiment Analysis of Product/Service Reviews
The main steps:

Define your problem (text based)
Upload your data (CSV with columns “Text” and “Label”)
Wait until a model for your problem is ready
Check results and test the model in the browser
Use the model through the Predict API endpoint

Visit for more insights!

Updated on: 06/05/2022

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