from sklearn.pipeline import Pipeline, FeatureUnion
from sklearn.model_selection import GridSearchCV
from sklearn.svm import SVC
from sklearn.datasets import load_iris
from sklearn.decomposition import PCA
from sklearn.feature_selection import SelectKBest

iris = load_iris()

X, y = iris.data, iris …

!python --version

Python 3.12.4

from constants import OPENAI_API_KEY

!pip show langchain-openai | grep "Version:"

Version: 0.2.9

import os

os.environ["OPENAI_API_KEY"] = OPENAI_API_KEY

from langchain_openai import ChatOpenAI

model = ChatOpenAI(model="gpt-4o-mini")

# https://python.langchain.com/docs/how_to/passthrough/

from langchain_community.vectorstores import FAISS
from langchain_core.output_parsers import …

!python --version

Python 3.12.4

from constants import OPENAI_API_KEY

!pip show langchain-openai | grep "Version:"

Version: 0.2.9

import os

os.environ["OPENAI_API_KEY"] = OPENAI_API_KEY

from langchain_openai import ChatOpenAI

model = ChatOpenAI(model="gpt-4o-mini")

from operator import itemgetter

from langchain_community.vectorstores import FAISS
from langchain_core.output_parsers import StrOutputParser
from langchain_core …

!python --version

Python 3.12.4

from constants import OPENAI_API_KEY

!pip show langchain-openai | grep "Version:"

Version: 0.2.9

import os

os.environ["OPENAI_API_KEY"] = OPENAI_API_KEY

from langchain_openai import ChatOpenAI …

import re

fh = open("sample_phone_book.txt")

for line in fh:
    if re.search(r"J.*Neu",line):
        print(line.rstrip())

    if re.search(r"a*Neu",line):
        print(line.rstrip())
fh.close()

Allison Neu 555-8396 …

# Created: 20250103

# https://pypi.org/project/Pint/0.24.4/

# !pip install pint

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 pint"))

requests==2.32 …

import tensorflow as tf

import os

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

# Initialize global variables

init_op = tf.global_variables_initializer()
session = tf.Session()
session.run(init_op)

a = tf.placeholder(tf.float32 …

import pandas as pd
import numpy as np

from plotnine import *

%matplotlib inline

df = pd.DataFrame({
    'variable': ['gender', 'gender', 'age', 'age', 'age', 'income', 'income', 'income', 'income'],
    'category': ['Female', 'Male', '1-24', '25-54', '55+', 'Lo', 'Lo-Med', 'Med', 'High …

from nltk.sentiment.vader import SentimentIntensityAnalyzer

def get_polorize_score(sentence):
    sid = SentimentIntensityAnalyzer()

    print(sentence)
    ss = sid.polarity_scores(sentence)

    return ss

print(get_polorize_score('very Good support for work.'))

very Good support for work.
{'neg': 0.0, 'neu': 0.327, 'pos …

from nltk.stem.porter import PorterStemmer

stemmer = PorterStemmer()

words =  [
    "radios",
    "colors",
    "mumbled"
]

words

['radios', 'colors', 'mumbled']

result = [stemmer.stem(word) for word in words]

result

['radio', 'color', 'mumbl']