<jupyter_start><jupyter_text>Import Libraries<jupyter_code>import pandas
import pycaret<jupyter_output><empty_output><jupyter_text>Load data into pycaret<jupyter_code>data=pandas.read_csv("training_data.csv",header='infer')
from pycaret.classification import *

s = setup(data, target = 'target',  log_experiment = True, experiment_name = 'psystock')<jupyter_output><empty_output><jupyter_text>Execute AutoML<jupyter_code>best = compare_models()
!mlflow ui<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.11522633744855967, 'fraction_numerical': 0.0, 'mean_word_length': 13.323529411764707, 'pattern_counts': {'":': 0, '<': 13, '<?xml version=': 0, '>': 13, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '3', 'dir': 'jupyter-structured-clean-dedup', 'id': '356399', 'license': 'MIT', 'n_tokens_mistral': 182, 'n_tokens_neox': 178, 'n_words': 23, 'path': 'Chapter12/automl_pycaret/automl_psystock_mlflow.ipynb', 'repo_name': 'waltatgit/Machine-Learning-Engineering-with-MLflow', 'size': '486'}