Develop a ML Model using Capsnet and CNN for Indoor Scenes Recognition
Budget: $30 – $250 USD
I am looking for a skilled machine learning developer to develop a ML model using Capsnet and CNN for indoor scenes recognition. The purpose of the ML model is scene recognition.
Dataset:
- The ML model will be trained using a pre-existing dataset.
Model Development:
- The model should be developed using pre-existing architectures but by modifying them to justify advancements in the current approach.
Ideal Skills and Experience:
- Strong knowledge and experience in machine learning and deep learning algorithms.
- Expertise in Capsnet and CNN architectures.
- Proficiency in working with pre-existing datasets and architectures.
- Ability to fine-tune and customize pre-existing architectures for optimal performance.
- Strong problem-solving skills and ability to optimize and improve the model's accuracy and efficiency.
Dataset:
- The ML model will be trained using a pre-existing dataset.
Model Development:
- The model should be developed using pre-existing architectures but by modifying them to justify advancements in the current approach.
Ideal Skills and Experience:
- Strong knowledge and experience in machine learning and deep learning algorithms.
- Expertise in Capsnet and CNN architectures.
- Proficiency in working with pre-existing datasets and architectures.
- Ability to fine-tune and customize pre-existing architectures for optimal performance.
- Strong problem-solving skills and ability to optimize and improve the model's accuracy and efficiency.