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

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视频 2021-12-31 19:39 2024-12-17 00:01 264 3.64 GB 83
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文件列表
  1. 1. Introduction/1. COURSE OVERVIEW LECTURE - PLEASE DO NOT SKIP!.mp434.41MB
  2. 1. Introduction/2. Installation and Environment Setup.mp499.12MB
  3. 1. Introduction/3. Course Curriculum.mp47.09MB
  4. 10. Atrium-Segmentation/1. 01-Introduction.mp447.79MB
  5. 10. Atrium-Segmentation/2. Preprocessing-01-Visualization.mp447.15MB
  6. 10. Atrium-Segmentation/3. Preprocessing-02-Processing.mp443.54MB
  7. 10. Atrium-Segmentation/4. Dataset-01-Dataset-Creation.mp440.42MB
  8. 10. Atrium-Segmentation/5. Dataset-02-Dataset-Validation.mp424.49MB
  9. 10. Atrium-Segmentation/6. UNet.mp464.46MB
  10. 10. Atrium-Segmentation/7. Train-01-Data-Loading-and-Loss.mp429.55MB
  11. 10. Atrium-Segmentation/8. Train-02-Model-Creation.mp450.65MB
  12. 10. Atrium-Segmentation/9. Train-03-Evaluation.mp463.43MB
  13. 11. Capstone-Project Lung Tumor Segmentation/1. Introduction.mp423.18MB
  14. 11. Capstone-Project Lung Tumor Segmentation/2. Overview.mp46.75MB
  15. 11. Capstone-Project Lung Tumor Segmentation/3. Oversampling.mp427.08MB
  16. 11. Capstone-Project Lung Tumor Segmentation/4. Discussion.mp427.08MB
  17. 12. 3D Liver and Liver Tumor Segmentation/1. Introduction.mp427.07MB
  18. 12. 3D Liver and Liver Tumor Segmentation/2. Data-Visualization.mp431.57MB
  19. 12. 3D Liver and Liver Tumor Segmentation/3. Model.mp426.26MB
  20. 12. 3D Liver and Liver Tumor Segmentation/4. Train-01-TorchIO-Dataset.mp459.83MB
  21. 12. 3D Liver and Liver Tumor Segmentation/5. Train-02-Model-Creation.mp435.78MB
  22. 12. 3D Liver and Liver Tumor Segmentation/6. Train-03-Evaluation.mp443.12MB
  23. 2. Crash Course NumPy/1. Introduction to NumPy.mp411.28MB
  24. 2. Crash Course NumPy/2. NumPy Arrays.mp450.81MB
  25. 2. Crash Course NumPy/3. NumPy Arrays Part Two.mp446.56MB
  26. 2. Crash Course NumPy/4. NumPy Index Selection.mp446.26MB
  27. 2. Crash Course NumPy/5. NumPy Operations.mp433.28MB
  28. 2. Crash Course NumPy/6. NumPy Exercises.mp411.54MB
  29. 2. Crash Course NumPy/7. NumPy Exercise - Solutions.mp448.56MB
  30. 3. Machine Learning Concepts Overview/1. What is Machine Learning.mp419.96MB
  31. 3. Machine Learning Concepts Overview/2. Supervised Learning.mp439.91MB
  32. 3. Machine Learning Concepts Overview/3. Overfitting.mp426.17MB
  33. 3. Machine Learning Concepts Overview/4. Evaluating Performance - Classification Error Metrics.mp482.45MB
  34. 3. Machine Learning Concepts Overview/5. Evaluating Performance - Regression Error Metrics.mp423.59MB
  35. 4. PyTorch Basics/1. PyTorch Basics Introduction.mp414.31MB
  36. 4. PyTorch Basics/2. Tensor Basics.mp435.17MB
  37. 4. PyTorch Basics/3. Tensor Basics-Part Two.mp466.82MB
  38. 4. PyTorch Basics/4. Tensor Operations.mp458.63MB
  39. 4. PyTorch Basics/5. Tensor Operations-Part Two.mp428.16MB
  40. 4. PyTorch Basics/6. PyTorch Basics - Exercise.mp415.19MB
  41. 4. PyTorch Basics/7. PyTorch Basics - Exercise Solutions.mp429.83MB
  42. 5. CNN - Convolutional Neural Networks/1. Introduction to CNNs.mp44.64MB
  43. 5. CNN - Convolutional Neural Networks/10. MNIST Data Revisited.mp49.19MB
  44. 5. CNN - Convolutional Neural Networks/11. MNIST with CNN - Code Along - Part One.mp4101.93MB
  45. 5. CNN - Convolutional Neural Networks/12. MNIST with CNN - Code Along - Part Two.mp487.52MB
  46. 5. CNN - Convolutional Neural Networks/13. MNIST with CNN - Code Along - Part Three.mp446.95MB
  47. 5. CNN - Convolutional Neural Networks/14. Why do we need GPUs.mp493MB
  48. 5. CNN - Convolutional Neural Networks/15. Using GPUs for PyTorch.mp496.5MB
  49. 5. CNN - Convolutional Neural Networks/2. Understanding the MNIST data set.mp414.38MB
  50. 5. CNN - Convolutional Neural Networks/3. ANN with MNIST - Part One - Data.mp497.88MB
  51. 5. CNN - Convolutional Neural Networks/4. ANN with MNIST - Part Two - Creating the Network.mp452.54MB
  52. 5. CNN - Convolutional Neural Networks/5. ANN with MNIST - Part Three - Training.mp478.16MB
  53. 5. CNN - Convolutional Neural Networks/6. ANN with MNIST - Part Four - Evaluation.mp450.19MB
  54. 5. CNN - Convolutional Neural Networks/7. Image Filters and Kernels.mp472.33MB
  55. 5. CNN - Convolutional Neural Networks/8. Convolutional Layers.mp457.99MB
  56. 5. CNN - Convolutional Neural Networks/9. Pooling Layers.mp427.64MB
  57. 6. Medical Imaging - A short Introduction/1. Introduction.mp423.71MB
  58. 6. Medical Imaging - A short Introduction/2. X-RAY.mp415.59MB
  59. 6. Medical Imaging - A short Introduction/3. CT.mp427.12MB
  60. 6. Medical Imaging - A short Introduction/4. MRI.mp417.98MB
  61. 6. Medical Imaging - A short Introduction/5. PET.mp414.16MB
  62. 7. Data Formats in Medical Imaging/1. Introduction.mp44.59MB
  63. 7. Data Formats in Medical Imaging/2. DICOM.mp420.05MB
  64. 7. Data Formats in Medical Imaging/3. DICOM-in-Python.mp489.01MB
  65. 7. Data Formats in Medical Imaging/4. NIfTI.mp410MB
  66. 7. Data Formats in Medical Imaging/5. NIfTI-in-Python.mp440.59MB
  67. 7. Data Formats in Medical Imaging/6. Preprocessing.mp465.06MB
  68. 7. Data Formats in Medical Imaging/7. Preprocessing-in-Python-Part-1.mp460.21MB
  69. 7. Data Formats in Medical Imaging/8. Preprocessing-in-Python-Part-2.mp460.32MB
  70. 8. Pneumonia-Classification/1. Introduction.mp455.37MB
  71. 8. Pneumonia-Classification/2. Preprocessing.mp486MB
  72. 8. Pneumonia-Classification/3. Train-01-Data-Loading.mp469.81MB
  73. 8. Pneumonia-Classification/4. Train-02-Model-Creation.mp482.82MB
  74. 8. Pneumonia-Classification/5. Train-03-Trainer.mp420.72MB
  75. 8. Pneumonia-Classification/6. Train-04-Evaluation.mp460.36MB
  76. 8. Pneumonia-Classification/7. Interpretability.mp4122.13MB
  77. 9. Cardiac-Detection/1. 01-Introduction.mp427.14MB
  78. 9. Cardiac-Detection/2. 02-Preprocessing.mp466.85MB
  79. 9. Cardiac-Detection/3. 03-Dataset-Part-1.mp457.35MB
  80. 9. Cardiac-Detection/4. 04-Dataset-Part-2.mp432.34MB
  81. 9. Cardiac-Detection/5. Train-01-Data-Loading.mp422.54MB
  82. 9. Cardiac-Detection/6. Train-02-Model-Creation.mp495.7MB
  83. 9. Cardiac-Detection/7. Train-03-Evaluation.mp442.57MB
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