Learn 3D Image Classification with Python and Keras

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Karthik K

1:06:18

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1. Fundamentals

1. Introduction.mp4

02:00

2. What is Computer Vision.mp4

00:37

3. What is 3D Image Classification .mp4

02:32

4. Our Project.mp4

01:56

5. How 3D Image Classification is done.mp4

01:40

6. Why Python and Keras.mp4

03:20

7. Why Google Colab.mp4

01:51

2. Model Building and Prediction

1. Create a 3d classification folder.mp4

00:32

2.1 no viral pneumonia part1.zip

2.2 no viral pneumonia part2.zip

2.3 with viral pneumonia part1.zip

2.4 with viral pneumonia part2.zip

2. Upload Dataset.mp4

02:22

3.1 code.zip

3. Python Code.mp4

01:14

4.1 ct weights.zip

4. Pre-Trained Model.mp4

01:35

5.1 prediction.zip

5. Prediction Folder.mp4

01:16

6. Enabling GPU in Google Colab.mp4

01:24

7. Is GPU connected to Colab notebook.mp4

01:16

8. Connect Google Colab with Google Drive.mp4

00:55

9. Import Libraries.mp4

02:05

10. Specify Directory.mp4

01:07

11. Check the number of CT scans.mp4

01:54

12. Visualize a Sample CT Scan.mp4

02:30

13. Preprocessing.mp4

03:49

14. Create Labels for the CT Scans.mp4

01:42

15. Splitting Data.mp4

03:04

16. Data Pre-Processing and Augmentation.mp4

03:30

17. Visualizing an Augmented CT Scan.mp4

02:50

18. Model Building.mp4

04:17

19. Visual Representation of 3D CNN.mp4

01:27

20. Model Compilation.mp4

02:44

21. Callbacks.mp4

02:20

22. Training.mp4

02:35

23. Loading Pre-Trained Weights.mp4

01:22

24. Prediction.mp4

04:32

Description

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.
Understanding of the architecture and parameters used in a 3D convolutional neural network.

Who is this for?

Anyone who is interested in learning about 3D image classification and building a 3D convolutional neural network using Python, Keras, and TensorFlow on the Google Colab platform.

AI enthusiasts who are eager to learn how to develop a deep learning model from scratch and want to apply their knowledge to the medical imaging domain.

Data scientists and machine learning engineers who are interested in expanding their skill set in the field of medical imaging analysis and want to work on real-world projects.

Healthcare professionals, such as radiologists and medical technicians, who are interested in utilizing advanced AI techniques to improve the accuracy of disease diagnosis from medical imaging data.

More details

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.
Medical imaging plays a vital role in disease diagnosis, and this course will provide you with the necessary skills and techniques to excel in this field. You will be able to tackle real-world challenges and gain a strong foundation in 3D image classification and deep learning. This is an excellent opportunity for healthcare professionals, data scientists, and anyone looking to advance their AI skills.
By the end of this course, you will have a complete understanding of how to classify 3D images using Python and Keras. You will have a portfolio project that you can showcase to potential employers and be able to confidently apply your skills in a professional setting. With its clear and concise approach, this course is designed to maximize your learning potential in the shortest time possible.
Enroll now and take the first step towards a fulfilling career in 3D image classification and AI. Happy Learning!
Who this course is for:
Anyone who is interested in learning about 3D image classification and building a 3D convolutional neural network using Python, Keras, and TensorFlow on the Google Colab platform.
AI enthusiasts who are eager to learn how to develop a deep learning model from scratch and want to apply their knowledge to the medical imaging domain.
Data scientists and machine learning engineers who are interested in expanding their skill set in the field of medical imaging analysis and want to work on real-world projects.
Healthcare professionals, such as radiologists and medical technicians, who are interested in utilizing advanced AI techniques to improve the accuracy of disease diagnosis from medical imaging data.

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Python

Karthik K

Instructor's Courses

Engineer dedicated to utilizing the power of Machine learning and Deep learning to solve real-world problems, improve design and performance assessment. Over ten years of experience in engineering and R&D environment. Engineering professional with a focus on Multi-physics CFD-ML from IIT Madras. Experienced in implementing action-oriented solutions to complex business problem.

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