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On this page
  • Sample Request
  • Building an Auto Text Classifier
  • Automated Model Construction
  • Sample Request
  • Training an Auto Image Classifier
  • Automated Model Training
  • Predictions

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  1. Autogon Engine (Studio)
  2. Automated Deep Learning

Auto Text Classification (A_DL_TXC)

This function creates an Automated Text classifying model

These models are designed to classify text into different categories, such as sentiment analysis or topic modeling.

Sample Request

Build an Auto Text Classifier

{
    "project_id": 1,
    "parent_id": 7,
    "block_id": 8,
    "function_code": "A_DL_TXC_I",
    "args": {
    "hyp_params":{
            "max_trials": 1
        }
    }
}

Building an Auto Text Classifier

Automated Model Construction

POST https://autogon.ai/api/v1/engine/start

Request Body

Name
Type
Description

project_id*

int

The id of the current project

block_id*

int

The id of the current block

function_code*

string

The function code for current block

parent_id*

int

The id of the previous block

args*

object

Block arguments

max_trials

int

Maximum number of different models that will be tried

{
    "status": "true",
    "message": {
        "id": 8,
        "project": 1,
        "block_id": 8,
        "parent_id": 7,
        "dataset_url": "",
        "x_value_url": "",
        "y_value_url": "",
        "x_train_url": "",
        "y_train_url": "",
        "x_test_url": "",
        "y_test_url": "",
        "output": {}
    }
}

Sample Request

Compile and train the pre-built TXC model, using passed in Hyper Parameters

{
    "project_id": 1,
    "parent_id": 8,
    "block_id": 9,
    "function_code": "A_DL_TXC_T",
    "args": {
        "model_name": "titanic_model",
        "hyp_params":{
            "epochs": 10
        }
    }
}

Training an Auto Image Classifier

Automated Model Training

POST https://autogon.ai/api/v1

Request Body

Name
Type
Description

project_id*

int

The id of the current project

hyp_params

object

hyper parameters for model compilation and training

parent_id*

int

The id of the previous block

block_id*

int

The id of the current block

function_code*

The function code for current block

args*

object

Block arguments

model_name*

String

The name the model would be saved with

epochs

int

Number of iterations through the dataset

{
    "status": "true",
    "message": {
        "id": 9,
        "project": 1,
        "block_id": 9,
        "parent_id": 8,
        "dataset_url": "",
        "x_value_url": "",
        "y_value_url": "",
        "x_train_url": "",
        "y_train_url": "",
        "x_test_url": "",
        "y_test_url": "",
        "output": {}
    }
}

Predictions

Make predictions with the DL_ANN Predict block

// Some code
// Some code
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Last updated 1 year ago

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