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种子名称： [FreeCourseSite.com] Udemy - Deep Learning with PyTorch for Medical Image Analysis
文件类型： 视频
文件数目： 83个文件
文件大小： 3.64 GB
收录时间： 2021-12-31 19:39
已经下载： 3次
资源热度： 250
最近下载： 2024-10-29 17:08

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[FreeCourseSite.com] Udemy - Deep Learning with PyTorch for Medical Image Analysis.torrent

1. Introduction/1. COURSE OVERVIEW LECTURE - PLEASE DO NOT SKIP!.mp434.41MB

1. Introduction/2. Installation and Environment Setup.mp499.12MB

1. Introduction/3. Course Curriculum.mp47.09MB

10. Atrium-Segmentation/1. 01-Introduction.mp447.79MB

10. Atrium-Segmentation/2. Preprocessing-01-Visualization.mp447.15MB

10. Atrium-Segmentation/3. Preprocessing-02-Processing.mp443.54MB

10. Atrium-Segmentation/4. Dataset-01-Dataset-Creation.mp440.42MB

10. Atrium-Segmentation/5. Dataset-02-Dataset-Validation.mp424.49MB

10. Atrium-Segmentation/6. UNet.mp464.46MB

10. Atrium-Segmentation/7. Train-01-Data-Loading-and-Loss.mp429.55MB

10. Atrium-Segmentation/8. Train-02-Model-Creation.mp450.65MB

10. Atrium-Segmentation/9. Train-03-Evaluation.mp463.43MB

11. Capstone-Project Lung Tumor Segmentation/1. Introduction.mp423.18MB

11. Capstone-Project Lung Tumor Segmentation/2. Overview.mp46.75MB

11. Capstone-Project Lung Tumor Segmentation/3. Oversampling.mp427.08MB

11. Capstone-Project Lung Tumor Segmentation/4. Discussion.mp427.08MB

12. 3D Liver and Liver Tumor Segmentation/1. Introduction.mp427.07MB

12. 3D Liver and Liver Tumor Segmentation/2. Data-Visualization.mp431.57MB

12. 3D Liver and Liver Tumor Segmentation/3. Model.mp426.26MB

12. 3D Liver and Liver Tumor Segmentation/4. Train-01-TorchIO-Dataset.mp459.83MB

12. 3D Liver and Liver Tumor Segmentation/5. Train-02-Model-Creation.mp435.78MB

12. 3D Liver and Liver Tumor Segmentation/6. Train-03-Evaluation.mp443.12MB

2. Crash Course NumPy/1. Introduction to NumPy.mp411.28MB

2. Crash Course NumPy/2. NumPy Arrays.mp450.81MB

2. Crash Course NumPy/3. NumPy Arrays Part Two.mp446.56MB

2. Crash Course NumPy/4. NumPy Index Selection.mp446.26MB

2. Crash Course NumPy/5. NumPy Operations.mp433.28MB

2. Crash Course NumPy/6. NumPy Exercises.mp411.54MB

2. Crash Course NumPy/7. NumPy Exercise - Solutions.mp448.56MB

3. Machine Learning Concepts Overview/1. What is Machine Learning.mp419.96MB

3. Machine Learning Concepts Overview/2. Supervised Learning.mp439.91MB

3. Machine Learning Concepts Overview/3. Overfitting.mp426.17MB

3. Machine Learning Concepts Overview/4. Evaluating Performance - Classification Error Metrics.mp482.45MB

3. Machine Learning Concepts Overview/5. Evaluating Performance - Regression Error Metrics.mp423.59MB

4. PyTorch Basics/1. PyTorch Basics Introduction.mp414.31MB

4. PyTorch Basics/2. Tensor Basics.mp435.17MB

4. PyTorch Basics/3. Tensor Basics-Part Two.mp466.82MB

4. PyTorch Basics/4. Tensor Operations.mp458.63MB

4. PyTorch Basics/5. Tensor Operations-Part Two.mp428.16MB

4. PyTorch Basics/6. PyTorch Basics - Exercise.mp415.19MB

4. PyTorch Basics/7. PyTorch Basics - Exercise Solutions.mp429.83MB

5. CNN - Convolutional Neural Networks/1. Introduction to CNNs.mp44.64MB

5. CNN - Convolutional Neural Networks/10. MNIST Data Revisited.mp49.19MB

5. CNN - Convolutional Neural Networks/11. MNIST with CNN - Code Along - Part One.mp4101.93MB

5. CNN - Convolutional Neural Networks/12. MNIST with CNN - Code Along - Part Two.mp487.52MB

5. CNN - Convolutional Neural Networks/13. MNIST with CNN - Code Along - Part Three.mp446.95MB

5. CNN - Convolutional Neural Networks/14. Why do we need GPUs.mp493MB

5. CNN - Convolutional Neural Networks/15. Using GPUs for PyTorch.mp496.5MB

5. CNN - Convolutional Neural Networks/2. Understanding the MNIST data set.mp414.38MB

5. CNN - Convolutional Neural Networks/3. ANN with MNIST - Part One - Data.mp497.88MB

5. CNN - Convolutional Neural Networks/4. ANN with MNIST - Part Two - Creating the Network.mp452.54MB

5. CNN - Convolutional Neural Networks/5. ANN with MNIST - Part Three - Training.mp478.16MB

5. CNN - Convolutional Neural Networks/6. ANN with MNIST - Part Four - Evaluation.mp450.19MB

5. CNN - Convolutional Neural Networks/7. Image Filters and Kernels.mp472.33MB

5. CNN - Convolutional Neural Networks/8. Convolutional Layers.mp457.99MB

5. CNN - Convolutional Neural Networks/9. Pooling Layers.mp427.64MB

6. Medical Imaging - A short Introduction/1. Introduction.mp423.71MB

6. Medical Imaging - A short Introduction/2. X-RAY.mp415.59MB

6. Medical Imaging - A short Introduction/3. CT.mp427.12MB

6. Medical Imaging - A short Introduction/4. MRI.mp417.98MB

6. Medical Imaging - A short Introduction/5. PET.mp414.16MB

7. Data Formats in Medical Imaging/1. Introduction.mp44.59MB

7. Data Formats in Medical Imaging/2. DICOM.mp420.05MB

7. Data Formats in Medical Imaging/3. DICOM-in-Python.mp489.01MB

7. Data Formats in Medical Imaging/4. NIfTI.mp410MB

7. Data Formats in Medical Imaging/5. NIfTI-in-Python.mp440.59MB

7. Data Formats in Medical Imaging/6. Preprocessing.mp465.06MB

7. Data Formats in Medical Imaging/7. Preprocessing-in-Python-Part-1.mp460.21MB

7. Data Formats in Medical Imaging/8. Preprocessing-in-Python-Part-2.mp460.32MB

8. Pneumonia-Classification/1. Introduction.mp455.37MB

8. Pneumonia-Classification/2. Preprocessing.mp486MB

8. Pneumonia-Classification/3. Train-01-Data-Loading.mp469.81MB

8. Pneumonia-Classification/4. Train-02-Model-Creation.mp482.82MB

8. Pneumonia-Classification/5. Train-03-Trainer.mp420.72MB

8. Pneumonia-Classification/6. Train-04-Evaluation.mp460.36MB

8. Pneumonia-Classification/7. Interpretability.mp4122.13MB

9. Cardiac-Detection/1. 01-Introduction.mp427.14MB

9. Cardiac-Detection/2. 02-Preprocessing.mp466.85MB

9. Cardiac-Detection/3. 03-Dataset-Part-1.mp457.35MB

9. Cardiac-Detection/4. 04-Dataset-Part-2.mp432.34MB

9. Cardiac-Detection/5. Train-01-Data-Loading.mp422.54MB

9. Cardiac-Detection/6. Train-02-Model-Creation.mp495.7MB

9. Cardiac-Detection/7. Train-03-Evaluation.mp442.57MB