AUtoML dataset

[priyanga24]

Hi Shashank,
I tried to use AutoML with a dataset that contains features extracted from PE files.

This is how basically my dataset will look like. I ran this with autogluon and it gave me good results. Is it true that autogluon can process datasets like these?
The one shown below is the data in one single cell under a column name 'datadir'. like these there are many rows and there are many other columns too which have subset of data like these.
[{'name': 'EXPORT_TABLE', 'size': 0, 'virtual_address': 0}, {'name': 'IMPORT_TABLE', 'size': 200, 'virtual_address': 35312}, {'name': 'RESOURCE_TABLE', 'size': 28672, 'virtual_address': 352256}, {'name': 'EXCEPTION_TABLE', 'size': 0, 'virtual_address': 0}, {'name': 'CERTIFICATE_TABLE', 'size': 0, 'virtual_address': 0}, {'name': 'BASE_RELOCATION_TABLE', 'size': 0, 'virtual_address': 0}, {'name': 'DEBUG', 'size': 0, 'virtual_address': 0}, {'name': 'ARCHITECTURE', 'size': 0, 'virtual_address': 0}, {'name': 'GLOBAL_PTR', 'size': 0, 'virtual_address': 0}, {'name': 'TLS_TABLE', 'size': 0, 'virtual_address': 0}, {'name': 'LOAD_CONFIG_TABLE', 'size': 72, 'virtual_address': 35240}, {'name': 'BOUND_IMPORT', 'size': 0, 'virtual_address': 0}, {'name': 'IAT', 'size': 660, 'virtual_address': 32768}, {'name': 'DELAY_IMPORT_DESCRIPTOR', 'size': 0, 'virtual_address': 0}, {'name': 'CLR_RUNTIME_HEADER', 'size': 0, 'virtual_address': 0}]
When i tried to run autogluon itself created many features and gave me good accuracy.
Is this working efficiently and correct? or i should change my data? Because autogluon's important characteristic is that it will itself take care of dataset like these. Please respond asap.thank you