Text Sentiment Analysis using Caikit and Hugging Face
|
Learn how to perform text sentiment analysis using Caikit and Hugging Face. Explore natural language processing (NLP) techniques to analyze and interpret emotions in text data.
At a Glance
In this guided project you will build a Python application that uses Caikit run-time and API to query the Hugging Face model for sentiment analysis on text strings.
Hugging Face provides an extensive collection of pre-trained models, allowing developers and researchers to leverage cutting-edge NLP and Generative AI capabilities with ease. The platform also offers user-friendly APIs, empowering users to integrate these models seamlessly into their own applications and projects.
A Look at the Project Ahead
- Installing the required Python libraries and Caikit run-time.
- Exploring Caikit and understanding its capabilities in the context of model management.
- Leveraging a Hugging Face model for sentiment classification.
- Implementing API calls to interact with the sentiment analysis model seamlessly.
What You’ll Need
User Reviews
Be the first to review “Text Sentiment Analysis using Caikit and Hugging Face”
Related Products
Building Generative Adversarial Networks
Learn to design and implement GANs for generating realistic data samples in various applications.
Introducing Generative AI with AWS
Learn the fundamentals of generative AI and how to implement AWS services to create AI-driven applications.
Ethical AI
Explore ethical considerations and frameworks for developing responsible AI systems that align with societal values.
Digital Arts and AI Tools Fluency
Gain proficiency in using AI tools for digital art creation, enhancing creativity and workflow.
Generative AI Fundamentals
Explore the core concepts of generative AI, including types, models, and use cases in various domains.
Natural Language Processing
Explore natural language processing methods to enable machines to understand and generate human language.
There are no reviews yet.