Are you looking for a high accuracy image classification model? I will build a custom CNN based image classifier using Python and deep learning that delivers production ready results.

I achieved a perfect score of 1.00000 on Kaggle in an image classification competition using ResNet50 with Transfer Learning ranking number 1 on the private leaderboard with 3000 out of 3000 images correctly classified. This proves my ability to build highly accurate deep learning models on real world datasets.

What you will get:

Trained CNN image classification model on your dataset

Data preprocessing and augmentation

Model evaluation with accuracy and loss report

Clean and well commented Python code

GitHub repository link

Working test script to run predictions

Techniques I use:

Transfer Learning with ResNet50 or VGG16

K-Fold Ensemble for higher accuracy

Data augmentation to prevent overfitting

Mixed precision training for faster results

Label smoothing and OneCycleLR scheduler

Who is this for:

Developers needing image recognition for their app

Researchers building custom vision datasets

Students working on computer vision projects

Businesses needing product or defect classification systems

Requirements from you:

Dataset with images organized in labeled folders or CSV format

Description of what needs to be classified

Lets build something accurate together!