Pro Deep Learning Engineer for CIFAR100 Classification - Highest Val Accuracy & Lowest Parameters/FLOPs
Budget: $30 – $100 AUD
I'm seeking a high-level Deep Learning Engineer to help classify CIFAR100 images. The ultimate goal is a strong position on the Kaggle leaderboard.
Key project requirements:
- Model Optimization: The model should prioritize achieving the highest accuracy while minimizing parameters and FLOPs. This requires a deep understanding of model complexity and performance trade-offs.
- Advanced Data Augmentation Techniques: The use of advanced data augmentation techniques is crucial. Specifically, I want to utilize methods like Cutout or Mixup to enhance the model's robustness and generalization capabilities.
- Convolutional Neural Network (CNN): The model should be based on a Convolutional Neural Network (CNN). Therefore, deep expertise in designing, implementing, and fine-tuning CNNs is required.
Ideal skills for this project include:
- Extensive experience in deep learning and computer vision.
- Proficiency in using Python and relevant libraries such as TensorFlow or PyTorch.
- Prior experience with CIFAR100 or similar datasets will be a plus.
- A proven track record of achieving high rankings on Kaggle competitions will be highly regarded.
Key project requirements:
- Model Optimization: The model should prioritize achieving the highest accuracy while minimizing parameters and FLOPs. This requires a deep understanding of model complexity and performance trade-offs.
- Advanced Data Augmentation Techniques: The use of advanced data augmentation techniques is crucial. Specifically, I want to utilize methods like Cutout or Mixup to enhance the model's robustness and generalization capabilities.
- Convolutional Neural Network (CNN): The model should be based on a Convolutional Neural Network (CNN). Therefore, deep expertise in designing, implementing, and fine-tuning CNNs is required.
Ideal skills for this project include:
- Extensive experience in deep learning and computer vision.
- Proficiency in using Python and relevant libraries such as TensorFlow or PyTorch.
- Prior experience with CIFAR100 or similar datasets will be a plus.
- A proven track record of achieving high rankings on Kaggle competitions will be highly regarded.