CIFAR-100 Model Optimization with PyTorch
Budget: $30 – $100 AUD
I'm looking for an expert in deep learning and PyTorch who can assist in fine-tuning a model on the CIFAR-100 dataset. The primary goal is to improve the model's accuracy through various techniques, including data augmentation, hyperparameter tuning, and adjustments to the model architecture.
Key Requirements:
- Extensive experience with PyTorch and deep learning
- Proven track record in model tuning
- Ability to implement data augmentation strategies
- Skilled in hyperparameter tuning
- Proficient in model architecture adjustments
I am open to suggestions for data augmentation and preprocessing steps, so a creative approach to enhancing the dataset is a plus. Please provide examples of previous similar projects you have worked on in your proposal.
Key Requirements:
- Extensive experience with PyTorch and deep learning
- Proven track record in model tuning
- Ability to implement data augmentation strategies
- Skilled in hyperparameter tuning
- Proficient in model architecture adjustments
I am open to suggestions for data augmentation and preprocessing steps, so a creative approach to enhancing the dataset is a plus. Please provide examples of previous similar projects you have worked on in your proposal.