Pneumonia Disease Classification | Machine Learning

Performed Steps:

• Got data from Kaggle public datasets.
• Configured TPU (Tensor Processing Unit).
• Performed preprocessing and image augmentation on data.
• Prepared data for training and validation.
• Build a model using transfer learning.
• Train and validate the model.
• Made predictions.

Project Details:

Python Version: 3.7

Packages: numpy, pandas, kaggle_datasets, tensorflow, keras, matplotlib, efficientnet, sklearn, seaborn, re, math, cv2, PIL, os.



Model: EfficientNet B6 (Transfer Learning with Imagenet weights).

Training Result:

• Recall: 0.9542
• Precision: 0.9881
• Accuracy: 0.9575

Validation Results:

• Recall: 0.9744
• Precision: 0.9870
• Accuracy: 0.9713

Predictions Accuracy: 88.30%

Code Previews:









For full source code please visit the GitHub repository.

Github Repository Link:

GitHub - zeeshan-akram/Pneumonia-Disease-Classification-CNN

GitHub - zeeshan-akram/Pneumonia-Disease-Classification-CNN

Contribute to zeeshan-akram/Pneumonia-Disease-Classification-CNN development by creating an account on GitHub.