import tensorflow as tf

import os

# Just disables the warning, doesn't enable AVX/FMA
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'

matrix1 = tf.constant([[3., 3.0]])
matrix2 = tf.constant([[2.0],[2.0]])
product = tf …

def odd_even():
    for i in range(10):      
        if i % 2 == 0:
              print(f"The number {i} is even")
        else:
            print(f"The number {i} is odd")

odd_even()

The number 0 is even
The number 1 is odd
The number 2 is even
The number 3 is odd
The number 4 …

def check_odd_or_even(input_number):

    if input_number % 2 == 0:
        return f"{input_number} is Even"

    return f"{input_number} is Odd"

check_odd_or_even(7)

'7 is Odd'

check_odd_or_even(8)

'8 is Even'

check_odd_or_even(0)

'0 is Even'

check_odd_or_even …

# Created: 20250103

import pyutil as pyu
pyu.get_local_pyinfo()

'conda env: ml312-2024; pyv: 3.12.7 | packaged by Anaconda, Inc. | (main, Oct  4 2024, 13:27:36) [GCC 11.2.0]'

print(pyu.ps2("requests"))

requests==2.32.3

import yfinance as yf
import pandas as pd
import numpy as …

import tensorflow as tf

import os

# Just disables the warning, doesn't enable AVX/FMA
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'

a = tf.ones([2, 5])

a

<tf.Tensor 'ones:0' shape=(2, 5) dtype=float32>

with tf.Session …

from PIL import Image
import numpy as np
import urllib.request

image_path = 'https://multimedia.bbycastatic.ca/multimedia/products/500x500/107/10736/10736343.jpg'

with urllib.request.urlopen(image_path) as url:
    with open('temp.jpg', 'wb …

import requests
from PIL import Image
from io import BytesIO

url = 'https://www.cognex.com/BarcodeGenerator/Content/images/isbn.png'

response = requests.get(url)
img = Image.open(BytesIO(response.content))

img

type(img)

PIL …

from PIL import Image
import numpy as np
import urllib.request

image_path = 'https://multimedia.bbycastatic.ca/multimedia/products/500x500/107/10736/10736343.jpg'

with urllib.request.urlopen(image_path) as url:
    with open('temp.jpg …

import re

names = ['M2N1H5', 'M2N 1H5', 'M882J8']

regex_patten = "^[A-Z]\d[A-Z]\s*\d[A-Z]\d"
# starts with Capital letter; it can have zero or one space

for name in names:
    m = re.match(regex_patten, name …

import pandas as pd

pd.__version__

'0.24.2'

pd.show_versions(as_json=False)

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.8.final.0
python-bits: 64
OS: Darwin
OS-release: 18.5.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL …