Text Classification using TensorFlow
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Text Classification using TensorFlow

Sentiment Analysis

Sentiment analysis is a crucial task in Natural Language Processing (NLP) that involves determining the emotional tone behind a text. It helps identify whether a given piece of text expresses a positive, negative, or neutral sentiment.

Some common applications of sentiment analysis include:

  • Customer Feedback Analysis: Companies analyze customer reviews to understand satisfaction levels.
  • Market Research: Analyzing public opinion about products or services.
  • Social Media Monitoring: Tracking sentiment trends on social platforms.
  • Brand Monitoring: Understanding how people perceive a brand online.
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apt update && apt install python3-pip python3 python3.10-venv -y

mkdir sentiment_attack
cd sentiment_attack
python3 -m venv venv
source venv/bin/activate

cat > requirements.txt <<EOF
torch==2.6.0
transformers==4.49.0
datasets==3.3.1
nltk==3.9.1
scikit-learn==1.6.1
tensorflow==2.15.0
tensorflow-hub==0.15.0
tensorflow-text==2.15.0
tf-keras==2.15.1
tensorflow-estimator==2.15.0
keras==2.15.0
textattack==0.3.10
EOF

pip install --upgrade pip
pip install -r requirements.txt