| 1. Create a “3d_classification” folder.mp4 | 1.8 MB | ||
| 1. Introduction.mp4 | 15.3 MB | ||
| 10. Specify Directory.mp4 | 3.4 MB | ||
| 11. Check the number of CT scans.mp4 | 9.4 MB | ||
| 12. Visualize a Sample CT Scan.mp4 | 16.1 MB | ||
| 13. Preprocessing.mp4 | 16.6 MB | ||
| 14. Create Labels for the CT Scans.mp4 | 4.8 MB | ||
| 15. Splitting Data.mp4 | 12.7 MB | ||
| 16. Data Pre-Processing and Augmentation.mp4 | 20.6 MB | ||
| 17. Visualizing an Augmented CT Scan.mp4 | 9.7 MB | ||
| 18. Model Building.mp4 | 32.5 MB | ||
| 19. Visual Representation of 3D CNN.mp4 | 4 MB | ||
| 2. Upload Dataset.mp4 | 6.3 MB | ||
| 2. What is Computer Vision.mp4 | 5.2 MB | ||
| 2.1 no_viral_pneumonia_part1.zip | 518 MB | ||
| 2.2 no_viral_pneumonia_part2.zip | 497.9 MB | ||
| 2.3 with_viral_pneumonia_part1.zip | 494.3 MB | ||
| 2.4 with_viral_pneumonia_part2.zip | 502.2 MB | ||
| 20. Model Compilation.mp4 | 9.1 MB | ||
| 21. Callbacks.mp4 | 7.1 MB | ||
| 22. Training.mp4 | 19.1 MB | ||
| 23. Loading Pre-Trained Weights.mp4 | 3 MB | ||
| 24. Prediction.mp4 | 26.9 MB | ||
| 3. Python Code.mp4 | 3.6 MB | ||
| 3. What is 3D Image Classification .mp4 | 18.5 MB | ||
| 3.1 code.ipynb | 513.4 KB | ||
| 4. Our Project.mp4 | 13.8 MB | ||
| 4. Pre-Trained Model.mp4 | 4.7 MB | ||
| 4.1 ct_weights.h5 | 15.6 MB | ||
| 5. How 3D Image Classification is done.mp4 | 7.7 MB | ||
| 5. Prediction Folder.mp4 | 2.8 MB | ||
| 5.1 prediction.zip | 20.2 MB | ||
| 6. Enabling GPU in Google Colab.mp4 | 6.3 MB | ||
| 6. Why Python and Keras.mp4 | 6 MB | ||
| 7. Is GPU connected to Colab notebook.mp4 | 4.8 MB | ||
| 7. Why Google Colab.mp4 | 3.6 MB | ||
| 8. Connect Google Colab with Google Drive.mp4 | 4.3 MB | ||
| 9. Import Libraries.mp4 | 7.2 MB | ||
| [Tutorialsplanet.NET].url | 102.4 B | ||
| ▲ 41 total files | |||
Udemy - Learn 3D Image Classification with Python and Keras [TP]
Learn to predict viral pneumonia in CT scans with the help of 3D CNNs in Python and Keras : Hands-on
What you'll learn
Understanding of 3D image classification and its applications in medical imaging, specifically in classifying viral pneumonia in CT scans.
Knowledge of how to use Python, Keras, and TensorFlow to build a 3D convolutional neural network (CNN) for image classification.
Hands-on experience in pre-processing and preparing 3D images for input into a machine learning model.Requirements
Basic knowledge of Python Programming
Description
Welcome to the "Learn 3D Image Classification with Python and Keras" course. In this comprehensive and hands-on course, you will learn how to build a powerful 3D convolutional neural network (CNN) for classifying CT scans. With the use of the Google Colab platform, Python, and Keras in TensorFlow, you will be able to effectively analyse medical images and predict the presence of viral pneumonia in computer tomography (CT) scans.
For more Udemy Courses: https://tutorialsplanet.net
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