<jupyter_start><jupyter_text><jupyter_code>import tensorflow as tf
import tensorflow.keras as keras
import tensorflow.keras.layers as layers
from tensorflow.keras.models import Sequential

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

from sklearn.preprocessing import OneHotEncoder
from sklearn.datasets import load_iris<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.04774535809018567, 'fraction_numerical': 0.0, 'mean_word_length': 7.217391304347826, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, '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': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '141579', 'license': 'Apache-2.0', 'n_tokens_mistral': 119, 'n_tokens_neox': 118, 'n_words': 36, 'path': 'ANNTemplate.ipynb', 'repo_name': 'srimanthtenneti/Tensorflow101', 'size': '377'}