This project provides basic Python examples for various Natural Language Processing (NLP) tasks with Docker.
These instructions will help you get the project up and running on your local machine for development and testing purposes.
List any prerequisites or dependencies that need to be installed before can use the project.
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Sentiment Analysis: Process of analyzing digital text to determine if the emotional tone of the message is positive, negative, or neutral.
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Named Entity Recognition: Identify entities (e.g., persons, organizations, locations) in a given sentence.
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Text Classification: Predict the category or class of a given piece of text.
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Text Summarization: Generate a summarized version of a longer piece of text (e.g., an article).
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Text Translation: Translate a sentence from one language to another.
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Pull Docker image
docker pull harshmanvar/basic-nlp:v1
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Run Docker image
docker run -it harshmanvar/basic-nlp:v1 <file-name.py>
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Sentiment Analysis Example :
docker run -it harshmanvar/basic-nlp:v1 01_sentiment_analysis.py
Enter your input
Enter the text for semantic analysis (type 'exit' to end): Docker is very cool tool..! Sentiment: Positive Enter the text for semantic analysis (type 'exit' to end): John is Idiot Sentiment: Negative Enter the text for semantic analysis (type 'exit' to end): Elephant Sentiment: Neutral
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Clone the repository
git clone https://github.com/harsh4870/Docker-NLP.git
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Install dependencies & Virtual env
python3 -m venv venv && pip install -r requirements.txt && source venv/bin/activate
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Run Examples:
Choose the specific task you want to run:
python 01_sentiment_analysis.py python 02_name_entity_recognition.py python 03_text_classification.py python 04_text_summarization.py python 05_language_translation.py
docker run -it harshmanvar/basic-nlp:v1 01_sentiment_analysis.pyEnter your input
Enter the text for semantic analysis (type 'exit' to end): Docker is very cool tool..!
Sentiment: Positive
Enter the text for semantic analysis (type 'exit' to end): John is Idiot
Sentiment: Negative
Enter the text for semantic analysis (type 'exit' to end): Elephant
Sentiment: Neutral
docker run -it harshmanvar/basic-nlp:v1 02_name_entity_recognition.pyEnter your input
Enter the text for entity recognition (type 'exit' to end): Apple Inc. is planning to open a new store in San Francisco. Tim Cook is the CEO of Apple.
Entity: Apple Inc., Type: ORG
Entity: San Francisco, Type: GPE
Entity: Tim Cook, Type: PERSON
Entity: Apple, Type: ORG
docker run -it harshmanvar/basic-nlp:v1 03_text_classification.pyEnter your input
Enter the text for classification (type 'exit' to end): Product is very Good
Accuracy: 1.00
Test Text (Positive): 'Product is very Good'
Predicted Sentiment: Positive
Enter the text for classification (type 'exit' to end): Product is not that good as per reviews
Accuracy: 1.00
Test Text (Positive): 'Product is not that good as per reviews'
Predicted Sentiment: Negative
docker run -it harshmanvar/basic-nlp:v1 04_text_summarization.pyEnter your input
Enter the text for summarization (type 'exit' to end): Artificial intelligence (AI) is a branch of computer science that aims to create machines capable of intelligent behavior. These machines are designed to mimic human cognitive functions such as learning, problem-solving, and decision-making. AI technologies can be classified into two main types: narrow or weak AI, which is designed for a particular task, and general or strong AI, which possesses the ability to understand, learn, and apply knowledge across various domains. One of the most popular approaches in AI is machine learning, where algorithms are trained on large datasets to recognize patterns and make predictions.
Artificial intelligence (AI) is a branch of computer science that aims to create machines capable of intelligent behavior. These machines are designed to mimic human cognitive functions such as learning, problem-solving, and decision-making.
docker run -it harshmanvar/basic-nlp:v1 05_language_translation.pyEnter your input
Enter the text for translation (type 'exit' to end): Hello, how are you doing?
Original Text: Hello, how are you doing?
Translated Text: Bonjour comment allez-vous?
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