Python Coder for Training Image Classification Models (VGG19, ResNet101, ResNet50, InceptionV3, AlexNet)
Budget: $250 – $750 USD
I'm seeking a Python coder to assist in training classification models on image data. Open-source code and datasets are readily available on Kaggle.
Key Responsibilities:
- Train 5 classification models using 70% of the data for training and 30% for testing.
- Implement the ADAMW optimizer with a learning rate of 0.0001.
- Utilize a batch size of either 16 or 32. Compare precision, accuracy, and F1 scores.
- Make results comparison of the following models with both datasets:
1. VGG19
2. Resnet101
3. Resnet50
4. InceptionV3
5. Alexnet
You are required to generate graphs of trainings Also generate confusion metrics of testing and classification reports.
Data Pre-processing:
- Normalize the image data.
- Apply data augmentation techniques.
- Resize the images as necessary.
Ideal skills and experience:
- Proficiency in Python and experience with image data processing.
- Familiarity with machine learning model training and the ADAMW optimizer.
- Experience with data normalization, augmentation, and resizing.
Key Responsibilities:
- Train 5 classification models using 70% of the data for training and 30% for testing.
- Implement the ADAMW optimizer with a learning rate of 0.0001.
- Utilize a batch size of either 16 or 32. Compare precision, accuracy, and F1 scores.
- Make results comparison of the following models with both datasets:
1. VGG19
2. Resnet101
3. Resnet50
4. InceptionV3
5. Alexnet
You are required to generate graphs of trainings Also generate confusion metrics of testing and classification reports.
Data Pre-processing:
- Normalize the image data.
- Apply data augmentation techniques.
- Resize the images as necessary.
Ideal skills and experience:
- Proficiency in Python and experience with image data processing.
- Familiarity with machine learning model training and the ADAMW optimizer.
- Experience with data normalization, augmentation, and resizing.