ML-capsule is a Project for beginners and experienced data science Enthusiasts who don't have a mentor or guidance and wish to learn Machine learning. Using our repo they can learn ML, DL, and many related technologies with different real-world projects and become Interview ready.
Description :- 1. Data Preparation: Collect and preprocess a balanced dataset of real and fake face images, including normalization, resizing, and augmentation.
Base Model Selection: EfficientNetB0,VGG16 , Xception , InceptionV3 like 5 different models excluding its top layers, to leverage its learned features.
Model Construction: Add custom layers on top of the base model for binary classification, compiling with appropriate loss and metrics.
Initial Training: Train the model with the base layers frozen to only update the new layers.
Fine-Tuning: Unfreeze some or all of the base model layers and continue training with a lower learning rate to fine-tune the entire network.
6.) EDA analysis.
7.) Comaprioson using performance matrices such as accuracy scores , confusion matrix etc.
Description :- 1. Data Preparation: Collect and preprocess a balanced dataset of real and fake face images, including normalization, resizing, and augmentation.
Fine-Tuning: Unfreeze some or all of the base model layers and continue training with a lower learning rate to fine-tune the entire network. 6.) EDA analysis. 7.) Comaprioson using performance matrices such as accuracy scores , confusion matrix etc.
Dataset I'll use :- https://www.kaggle.com/datasets/vencerlanz09/insect-village-synthetic-dataset
@Niketkumardheeryan @invigorzz313 kindly asiign this issue to me.