Project

class Project(object)

This namespace represents a project in DS2.ai's desktop application, specifically CLICK AI, which is for AI modeling.

init()

__init__(info, user)

Parmeters

• info (str) : Information about the current Click AI project corresponding to the object

• user (str) : User for creating, modifying, deleting the project

Fields

• id : Project ID.

• url : DS2 API url information.

• user : User information.

• user_token : User token information.

• status

• dataconnectorList

• models

• jupyter_servers

repr()

Returns the Click AI's project ID as a printable format.

__repr__()

Return type

• str

refresh()

Reads and refresh Project id, and check whether the project is ready to use.

modify()

Return type

• class CLICKAI project

delete()

Deletes the Project object that has corresponding project id and token.

delete()

Return type

• None

Reference

• You can find the corresponding project id deleted.

train()

Starts AI training according to the corresponding training method, value for prediction, and training option.

startTraining(training_method=None, value_for_predict=None, option="accuracy")

Parmeters

• training_method (str) : One of the suitable training methods with your data from 'cycle_gan', 'image', 'normal_classification', 'normal_regression', 'object_detection', 'time_series', 'time_series_regression', 'time_series_classification', 'recommender' or 'image_classification'.

• value_for_predict (str): When the format of data_file is .csv, result column name. (if has_label_data is "True", input the column name the data file has, if "False", enter an name you want as the result column name) When the format of data_file is not .csv, leave as default value.

• option (str): One of the training options, 'accuracy' for higher accuracy, or 'speed' for faster training speed.

Return type

• Project object

Reference

The project has been started.

stop()

Stops the ongoing AI training.

stop()

Return type

• Project object

get_magic_code()

Makes a new ipynb file to the designated file path and writes the needed code for AI modeling.

get_magic_code(training_method, value_for_predict, file_path="output.ipynb")

Parameters

• training_method (str): Training method as a string.

• value_for_predict (str): User for making the data connector corresponding to the object.

• file_path (str): Designated file path for saving ipynb file.

Return type

• None