A mood classification is a type of machine learning task that is used to recognize human moods or emotions based on input data, such as text, images, audio, or physiological signs. It's designed to automatically determine the emotional state or mood of an individual from the provided input.
Mood classification has various applications.
- sentiment analysis in customer feedback
- recommendation systems
- personalized user experiences
- mental health monitoring
For this project stackholders possibly be
- Any retail store
- Banks
- Mental health professionals
- Academic and reseach institutions
I will be using the Happy House dataset for this project, which contains images of peaoples' faces.
- Tensorflow
- Keras' Sequential API
I have used TensorFlow framework for this project.
pip install tensorflow- TensorFlow
- Keras
- Saving and reusing models