LSTMs are particularly effective for tasks involving sequential data, such as text classification, where the order and context of words are important. They can capture long-term dependencies and maintain relevant information over time, making them well-suited for processing and understanding textual data.

• constants
• config_enity
• artifact_enity
• components
• pipeline
• app.py

conda create -p hate python=3.10 -y

conda init
conda activate D:\Text-classification\hate

conda activate hate

pip install -r requirements.txt

https://dl.google.com/dl/cloudsdk/channels/rapid/GoogleCloudSDKInstaller.exe

gcloud init

python app.py