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Modern Artificial Intelligence Masterclass Build 6 Projects

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视频 2024-1-10 03:48 2024-5-16 02:33 725 8.42 GB 84
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Modern Artificial Intelligence Masterclass Build 6 Projects

文件列表
  1. 3. Emotion AI/7. Task #6 - Understand Artificial Neural Networks (ANNs) Theory & Intuition.mp4219.47MB
  2. 4. AI in Healthcare/1. Project Introduction and Welcome Message.mp458.01MB
  3. 4. AI in Healthcare/7. Task #6 - Train a Classifier Model To Detect Brain Tumors.mp4201.36MB
  4. 4. AI in Healthcare/5. Task #4 - Understand the Intuition behind ResNet and CNNs.mp4122.27MB
  5. 4. AI in Healthcare/4. Task #3 - Visualize and Explore Datasets.mp4164.87MB
  6. 4. AI in Healthcare/3. Task #2 - Import Libraries and Datasets.mp4107.07MB
  7. 4. AI in Healthcare/11. Task #10 - Train ResUnet Segmentation Model.mp438.29MB
  8. 4. AI in Healthcare/9. Task #8 - Understand ResUnet Segmentation Models Intuition.mp4150.52MB
  9. 4. AI in Healthcare/10. Task #9 - Build a Segmentation Model to Localize Brain Tumors.mp4136.71MB
  10. 4. AI in Healthcare/8. Task #7 - Assess Trained Classifier Model Performance.mp479.19MB
  11. 4. AI in Healthcare/2. Task #1 - Understand the Problem Statement and Business Case.mp4175.95MB
  12. 4. AI in Healthcare/6. Task #5 - Understand Theory and Intuition Behind Transfer Learning.mp4120.68MB
  13. 6. AI In Business (Finance) & AutoML/7. Task #5 - Understand the Theory & Intuition Behind XG-Boost Algorithm.mp4212.63MB
  14. 6. AI In Business (Finance) & AutoML/11. Task #9 - Understand XG-Boost in AWS SageMaker.mp477.68MB
  15. 6. AI In Business (Finance) & AutoML/1. Project Introduction and Welcome Message.mp456.98MB
  16. 6. AI In Business (Finance) & AutoML/9. Task #7 - Train XG-Boost Algorithm Using Scikit-Learn.mp471.48MB
  17. 6. AI In Business (Finance) & AutoML/6. Task #4 - Clean Up the Data.mp455.6MB
  18. 6. AI In Business (Finance) & AutoML/13. Task #11 - Deploy Model and Make Inference.mp4107.9MB
  19. 6. AI In Business (Finance) & AutoML/10. Task #8 - Perform Grid Search and Hyper-parameters Optimization.mp465.7MB
  20. 6. AI In Business (Finance) & AutoML/5. Task #3 - Visualize and Explore Dataset.mp4199.67MB
  21. 6. AI In Business (Finance) & AutoML/12. Task #10 - Train XG-Boost in AWS SageMaker.mp4140.4MB
  22. 6. AI In Business (Finance) & AutoML/8. Task #6 - Understand XG-Boost Algorithm Key Steps.mp4205.48MB
  23. 6. AI In Business (Finance) & AutoML/4. Task #2 - Import Libraries and Datasets.mp451.86MB
  24. 6. AI In Business (Finance) & AutoML/14. Task #12 - Train and Deploy Model Using AWS AutoPilot (Minimal Coding Required!).mp4122.81MB
  25. 6. AI In Business (Finance) & AutoML/3. Task #1 - Understand the Problem Statement & Business Case.mp4105.46MB
  26. 7. Creative AI/1. Project Introduction and Welcome Message.mp437.07MB
  27. 7. Creative AI/2. Task #1 - Understand the Problem Statement & Business Case.mp4136.85MB
  28. 7. Creative AI/10. Task #9 - Apply DeepDream Algorithm to Generate Images.mp466.9MB
  29. 7. Creative AI/9. Task #8 - Implement Deep Dream Algorithm Part #2.mp4120.75MB
  30. 7. Creative AI/3. Task #2 - Import Model with Pre-trained Weights.mp453.87MB
  31. 7. Creative AI/4. Task #3 - Import and Merge Images.mp467.98MB
  32. 7. Creative AI/6. Task #5 - Understand the Theory & Intuition Behind Deep Dream Algorithm.mp4195.03MB
  33. 7. Creative AI/11. Task #10 - Generate DeepDream Video.mp477.81MB
  34. 7. Creative AI/7. Task #6 - Understand The Gradient Operations in TF 2.0.mp437.47MB
  35. 7. Creative AI/5. Task #4 - Run the Pre-trained Model and Explore Activations.mp485.05MB
  36. 7. Creative AI/8. Task #7 - Implement Deep Dream Algorithm Part #1.mp483.08MB
  37. 8. Explainable AI/1. Project Introduction and Welcome Message.mp439.61MB
  38. 9. Crash Course on AWS, S3, and SageMaker/7. AWS SageMaker Overview.mp464.64MB
  39. 9. Crash Course on AWS, S3, and SageMaker/2. Key Machine Learning Components and AWS Tour.mp460.76MB
  40. 9. Crash Course on AWS, S3, and SageMaker/5. EC2 and Identity and Access Management (IAM).mp4108.29MB
  41. 9. Crash Course on AWS, S3, and SageMaker/4. Amazon S3.mp4111.36MB
  42. 9. Crash Course on AWS, S3, and SageMaker/3. Regions and Availability Zones.mp452.94MB
  43. 9. Crash Course on AWS, S3, and SageMaker/9. AWS SageMaker Studio Overview.mp466.93MB
  44. 9. Crash Course on AWS, S3, and SageMaker/6. AWS Free Tier Account Setup and Overview.mp438.11MB
  45. 9. Crash Course on AWS, S3, and SageMaker/1. What is AWS and Cloud Computing.mp468.06MB
  46. 9. Crash Course on AWS, S3, and SageMaker/8. AWS SageMaker Walk-through.mp481.6MB
  47. 9. Crash Course on AWS, S3, and SageMaker/11. AWS SageMaker Model Deployment.mp4110.86MB
  48. 9. Crash Course on AWS, S3, and SageMaker/10. AWS SageMaker Studio Walk-through.mp451.51MB
  49. 3. Emotion AI/9. Task #8 - Understand Convolutional Neural Networks and ResNets.mp4127.04MB
  50. 3. Emotion AI/10. Task #9 - Build ResNet to Detect Key Facial Points.mp4131.85MB
  51. 3. Emotion AI/1. Project Introduction and Welcome Message.mp461.4MB
  52. 3. Emotion AI/2. Task #1 - Understand the Problem Statement & Business Case.mp4118.88MB
  53. 3. Emotion AI/13. Task #12 - Import and Explore Facial Expressions (Emotions) Datasets.mp494.82MB
  54. 3. Emotion AI/15. Task #14 - Perform Image Augmentation.mp4109.35MB
  55. 3. Emotion AI/21. Task #20 - Serve Trained Model in TensorFlow 2.0 Serving.mp441.17MB
  56. 3. Emotion AI/17. Task #16 - Understand Classifiers Key Performance Indicators (KPIs).mp4135.26MB
  57. 3. Emotion AI/16. Task #15 - Build & Train a Facial Expression Classifier Model.mp4138.26MB
  58. 3. Emotion AI/8. Task #7 - Understand ANNs Training & Gradient Descent Algorithm.mp4160.52MB
  59. 3. Emotion AI/3. Task #2 - Import Libraries and Datasets.mp4102.22MB
  60. 3. Emotion AI/14. Task #13 - Visualize Images for Facial Expression Detection.mp455.97MB
  61. 3. Emotion AI/20. Task #19 - Save Trained Model for Deployment.mp4101.84MB
  62. 3. Emotion AI/22. Task #21 - Deploy Both Models and Make Inference.mp488.5MB
  63. 4. AI in Healthcare/12. Task #11 - Assess Trained ResUNet Segmentation Model Performance.mp4128.67MB
  64. 3. Emotion AI/5. Task #4 - Perform Images Augmentation.mp4141.82MB
  65. 3. Emotion AI/18. Task #17 - Assess Facial Expression Classifier Model.mp4104.52MB
  66. 3. Emotion AI/12. Task #11 - Assess Trained ResNet Model Performance.mp442.91MB
  67. 3. Emotion AI/6. Task #5 - Perform Data Normalization and Scaling.mp459.34MB
  68. 3. Emotion AI/19. Task #18 - Make Predictions from Both Models 1. Key Facial Points & 2. Emotion.mp460.04MB
  69. 3. Emotion AI/4. Task #3 - Perform Image Visualizations.mp487.34MB
  70. 3. Emotion AI/11. Task #10 - Compile and Train Facial Key Points Detector Model.mp468.11MB
  71. 1. Introduction/1. Introduction and Welcome Message.mp469.17MB
  72. 1. Introduction/3. Course Outline and Key Learning Outcomes.mp4174.78MB
  73. 1. Introduction/2. Introduction, Key Tips and Best Practices.mp4108.49MB
  74. 5. AI in Business (Marketing)/8. Task #7 - Apply K-Means Clustering Algorithm.mp4145.46MB
  75. 5. AI in Business (Marketing)/1. Project Introduction and Welcome Message.mp446.85MB
  76. 5. AI in Business (Marketing)/4. Task #3 - Perform Exploratory Data Analysis (Part #1).mp4132.99MB
  77. 5. AI in Business (Marketing)/7. Apply Elbow Method to Find the Optimal Number of Clusters.mp472.65MB
  78. 5. AI in Business (Marketing)/3. Task #2 - Import Libraries and Datasets.mp4106.54MB
  79. 5. AI in Business (Marketing)/9. Task #8 - Understand Intuition Behind Principal Component Analysis (PCA).mp4100.97MB
  80. 5. AI in Business (Marketing)/5. Task #4 - Perform Exploratory Data Analysis (Part #2).mp4182.96MB
  81. 5. AI in Business (Marketing)/6. Task #5 - Understand Theory and Intuition Behind K-Means Clustering Algorithm.mp4165.3MB
  82. 5. AI in Business (Marketing)/11. Task #10 - Apply Auto-encoders and Perform Clustering.mp4135.32MB
  83. 5. AI in Business (Marketing)/10. Task #9 - Understand the Theory and Intuition Behind Auto-encoders.mp483.04MB
  84. 5. AI in Business (Marketing)/2. Task #1 - Understand AI Applications in Marketing.mp473.74MB
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