This is a sentiment analysis project with python and machine learning
Required Libraries:
The following Python libraries are required to run the code:
pandas (import pandas as pd): Data manipulation and analysis.
numpy (import numpy as np): Numerical operations and array manipulation.
nltk (import nltk): Natural Language Toolkit for text processing.
re (import re): Regular expressions for string manipulation.
string (import string): String manipulation operations.
stopwords (from nltk.corpus import stopwords): Stopwords for text cleaning.
PorterStemmer (from nltk.stem.porter import PorterStemmer): Stemming algorithm for word normalization.
CountVectorizer (from sklearn.feature_extraction.text import CountVectorizer): Feature extraction for text data.
LogisticRegression (from sklearn.linear_model import LogisticRegression): Logistic regression model for classification.
f1_score, accuracy_score (from sklearn.metrics import f1_score, accuracy_score): Evaluation metrics for classification models.
WordCloud (from wordcloud import WordCloud): Visualization of word frequencies.
matplotlib.pyplot (import matplotlib.pyplot as plt): Data visualization library.
seaborn (import seaborn as sns): Data visualization library built on top of matplotlib.
warnings (import warnings): Handling warnings in the code.