<jupyter_start><jupyter_text><jupyter_code>import numpy as np
m=np.matrix([[1,2,3],[4,5,6],[7,8,9]])
m
m.T
from numpy.linalg import inv
a = np.array([[1., 2.], [3., 4.]])
inv(np.matrix(a))
import numpy.linalg
numpy.linalg.det(a)
numpy.linalg.eigvals(m)
np.linalg.norm(a)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.22333333333333333, 'fraction_numerical': 0.043333333333333335, 'mean_word_length': 6.717948717948718, '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': '624531', 'license': 'MIT', 'n_tokens_mistral': 156, 'n_tokens_neox': 151, 'n_words': 22, 'path': 'Matrices_GettingStarted.ipynb', 'repo_name': 'bharathulaprasad/cs360ml', 'size': '300'}