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340 - AWS Certified Machine Learning - Specialty

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视频 2020-9-2 21:30 2024-7-1 12:50 130 5 GB 95
磁力链接
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迅雷链接
thunder://QUFtYWduZXQ6P3h0PXVybjpidGloOjVhNDFkNzJlMDUzY2I1ZDVhNmQ3MTkzYjgwN2FmYzQ4M2U0OTllNmZaWg==
二维码链接
340 - AWS Certified Machine Learning - Specialty的二维码
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相关链接

340 - AWS Certified Machine Learning - Specialty

文件列表
  1. 001 - Course Introduction.mp440.88MB
  2. 002 - About the Training Architect.mp421.76MB
  3. 003 - About the Exam.mp4152.23MB
  4. 004 - Artificial Intelligence.mp421.17MB
  5. 005 - What Is Machine Learning?.mp440.75MB
  6. 006 - What Is Deep Learning?.mp438.57MB
  7. 007 - Section Introduction.mp411.25MB
  8. 008 - Machine Learning Lifecycle.mp459.8MB
  9. 009 - Supervised, Unsupervised, and Reinforcement.mp440.67MB
  10. 010 - Optimization.mp431.59MB
  11. 011 - Regularization.mp415.99MB
  12. 012 - Hyperparameters.mp424.14MB
  13. 013 - Validation.mp414.97MB
  14. 014 - Section Introduction.mp49.75MB
  15. 015 - Feature Selection and Engineering.mp435.56MB
  16. 016 - Principal Component Analysis (PCA).mp440.5MB
  17. 017 - Missing and Unbalanced Data.mp443.4MB
  18. 018 - Label and One Hot Encoding.mp414.79MB
  19. 019 - Splitting and Randomization.mp416.63MB
  20. 020 - RecordIO Format.mp421.1MB
  21. 021 - Section Introduction.mp48.12MB
  22. 022 - Logistical Regression.mp432.31MB
  23. 023 - Linear Regression.mp424.26MB
  24. 024 - Support Vector Machines.mp421.53MB
  25. 025 - Decision Trees.mp438.69MB
  26. 026 - Random Forests.mp425.95MB
  27. 027 - K-Means.mp433.84MB
  28. 028 - K-Nearest Neighbour.mp413.83MB
  29. 029 - Latent Dirichlet Allocation (LDA) Algorithm.mp438.9MB
  30. 030 - Section Introduction.mp47.99MB
  31. 031 - Neural Networks.mp471.87MB
  32. 032 - Convolutional Neural Networks (CNN).mp445.07MB
  33. 033 - Recurrent Neural Networks (RNN).mp441.96MB
  34. 034 - Section Introduction.mp417.04MB
  35. 035 - Confusion Matrix.mp449MB
  36. 036 - Sensitivity and Specificity.mp484.23MB
  37. 037 - Accuracy and Precision.mp431.64MB
  38. 038 - ROC_AUC.mp469.45MB
  39. 039 - Gini Impurity.mp435.11MB
  40. 040 - F1 Score.mp425.38MB
  41. 041 - Introduction to Jupyter Notebooks.mp466.91MB
  42. 042 - ML and DL Frameworks.mp440.28MB
  43. 043 - TensorFlow.mp483.18MB
  44. 044 - PyTorch.mp439.69MB
  45. 045 - MXNet.mp432.39MB
  46. 046 - Scikit-learn.mp494.28MB
  47. 047 - S3.mp490.6MB
  48. 048 - Glue.mp483.87MB
  49. 049 - Athena.mp486.56MB
  50. 050 - QuickSight.mp447.42MB
  51. 051 - Kinesis, Streams, Firehose, Video, and Analytics.mp482.27MB
  52. 052 - EMR with Spark.mp432.85MB
  53. 053 - EC2 for ML.mp460.82MB
  54. 054 - Amazon ML.mp413.03MB
  55. 055 - Section Introduction.mp437.5MB
  56. 056 - Amazon Rekognition (Images) Part 1.mp490.78MB
  57. 057 - Amazon Rekognition (Images) Part 2 - the API.mp4161.34MB
  58. 058 - Amazon Rekognition (Video).mp448.47MB
  59. 059 - Amazon Polly.mp452.04MB
  60. 060 - Amazon Transcribe.mp453.32MB
  61. 061 - Amazon Translate.mp488.63MB
  62. 062 - Amazon Comprehend.mp471.78MB
  63. 063 - Amazon Lex.mp477.77MB
  64. 064 - Amazon Service Chaining with AWS Step Functions.mp466.14MB
  65. 065 - Section Introduction.mp419.05MB
  66. 066 - What is Amazon SageMaker?.mp439.73MB
  67. 067 - The Three Stages.mp413.36MB
  68. 068 - Control (Console_SDK_Notebooks).mp484.27MB
  69. 069 - SageMaker Notebooks.mp495.83MB
  70. 070 - Data Preprocessing.mp459.61MB
  71. 071 - Ground Truth.mp440.26MB
  72. 072 - Preprocessing Image Data (Pinehead NotPinehead).mp4192.2MB
  73. 073 - Algorithms.mp469.62MB
  74. 074 - SageMaker Algorithms - Architecture 1.mp452.83MB
  75. 075 - SageMaker Algorithms - Architecture 2.mp448.95MB
  76. 076 - SageMaker Algorithms - Architecture 3.mp423.65MB
  77. 077 - Training an Image Classifier - Part 1 (Pinehead NotPinehead).mp4126.75MB
  78. 078 - Training an Image Classifier - Part 2 (Pinehead NotPinehead).mp431.65MB
  79. 079 - Hyperparameter Tuning.mp457.57MB
  80. 080 - Inference Pipelines.mp418.2MB
  81. 081 - Real-Time and Batch Inference.mp424.18MB
  82. 082 - Deploy an Image Classifier (Pinehead, NotPinehead).mp4110.49MB
  83. 083 - Accessing Inference from Apps.mp416.97MB
  84. 084 - Create a custom API for inference - Part 1 (Pinehead NotPinehead).mp465.2MB
  85. 085 - Create a custom API for inference - Part 2 (Pinehead NotPinehead).mp4105.93MB
  86. 086 - Securing SageMaker Notebooks.mp4112.56MB
  87. 087 - SageMaker and the VPC.mp423.12MB
  88. 088 - Section Introduction.mp410.16MB
  89. 089 - DeepLens - Part 1.mp4171.78MB
  90. 090 - DeepLens - Part 2.mp450.88MB
  91. 091 - DeepRacer - Part 1.mp4175.45MB
  92. 092 - DeepRacer - Part 2.mp438.74MB
  93. 093 - How to Answer Questions.mp4119.63MB
  94. 094 - How to Prepare.mp462.68MB
  95. 095 - Goodbye!.mp440.43MB
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