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AWS SageMaker Practical for Beginners. Build 6 Projects

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  • 文件大小:9GB
  • 下载次数:6
  • 最近下载:2021-01-21 22:14:37
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文件列表

  1. 3 - Project #1 - Employee Salary Predictions Using AWS SageMaker Linear Learner/30 - Coding Task #7 - Train a Linear Learner Model in AWS SageMaker.mp4 484MB
  2. 4 - Project #2 - Medical Insurance Premium Prediction/41 - Coding Task #7 - Train a Linear Learner Model in AWS SageMaker.mp4 344MB
  3. 4 - Project #2 - Medical Insurance Premium Prediction/49 - Coding Task #9 - Train Artificial Neural Networks for Regression Tasks.mp4 250MB
  4. 6 - Project #4 - Predict Cardiovascular Disease Using PCA & XGBoost (Classification)/81 - Coding Task #6 - Train & Test XGboost and Perform Grid Search (Local Mode).mp4 229MB
  5. 5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/61 - Coding Task #1 #2 #3 - Load Dataset_Libraries and Perform Data Exploration.mp4 225MB
  6. 6 - Project #4 - Predict Cardiovascular Disease Using PCA & XGBoost (Classification)/75 - Precision, Recall, and F1-Score.mp4 207MB
  7. 7 - Project #5 - Deep Learning for Traffic Sign Classification Using AWS SageMaker/95 - Coding Task #5 - Build and Train CNNs.mp4 206MB
  8. 5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/64 - Coding Task #6 #7 - Visualize Dataset.mp4 205MB
  9. 3 - Project #1 - Employee Salary Predictions Using AWS SageMaker Linear Learner/23 - Coding Task #1A - Instantiate AWS SageMaker Notebook Instance (Method #1).mp4 195MB
  10. 5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/57 - Gradient Boosted Trees - Deep Dive - Part #1.mp4 180MB
  11. 5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/67 - Coding Task #10 - Train XGBoost Using SageMaker.mp4 176MB
  12. 3 - Project #1 - Employee Salary Predictions Using AWS SageMaker Linear Learner/22 - AWS SageMaker Linear Learner Overview.mp4 168MB
  13. 5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/69 - Coding Task #12 - Perform Hyperparameters Tuning.mp4 166MB
  14. 4 - Project #2 - Medical Insurance Premium Prediction/37 - Coding Task #3 - Perform Exploratory Data Analysis.mp4 158MB
  15. 7 - Project #5 - Deep Learning for Traffic Sign Classification Using AWS SageMaker/93 - Coding Part #1 #2 - Import Images and Visualize Them.mp4 158MB
  16. 1 - Introduction, Success Tips & Best Practices and Key Learning Outcomes/04 - Course Outline and Key Learning Outcomes.mp4 156MB
  17. 6 - Project #4 - Predict Cardiovascular Disease Using PCA & XGBoost (Classification)/82 - Coding Task #7 - Train a PCA Model in AWS SageMaker.mp4 156MB
  18. SageMaker+Practical+Course+Package.zip 145MB
  19. 3 - Project #1 - Employee Salary Predictions Using AWS SageMaker Linear Learner/26 - Coding Task #3 - Perform Exploratory Data Analysis.mp4 144MB
  20. 4 - Project #2 - Medical Insurance Premium Prediction/36 - Coding Task #1 & #2 - Import Dataset and Key Libraries.mp4 136MB
  21. 2 - Introduction to AI_ML, AWS and Cloud Computing/18 - SageMaker Models Deployment.mp4 134MB
  22. 3 - Project #1 - Employee Salary Predictions Using AWS SageMaker Linear Learner/31 - Coding Task #8 - Deploy Model & invoke endpoint in SageMaker.mp4 125MB
  23. 7 - Project #5 - Deep Learning for Traffic Sign Classification Using AWS SageMaker/88 - What are Convolutional Neural Networks and How do they Learn - Part #2.mp4 124MB
  24. 2 - Introduction to AI_ML, AWS and Cloud Computing/15 - AWS SageMaker Walk-through.mp4 118MB
  25. 7 - Project #5 - Deep Learning for Traffic Sign Classification Using AWS SageMaker/87 - What are Convolutional Neural Networks and How do they Learn - Part #1.mp4 118MB
  26. 6 - Project #4 - Predict Cardiovascular Disease Using PCA & XGBoost (Classification)/84 - Coding Task #9 - Train XGBoost (SageMaker Built-in) to do Classification Tasks.mp4 115MB
  27. 4 - Project #2 - Medical Insurance Premium Prediction/38 - Coding Task #4 - Perform Data Visualization.mp4 113MB
  28. 6 - Project #4 - Predict Cardiovascular Disease Using PCA & XGBoost (Classification)/72 - Principal Component Analysis (PCA) Intuition.mp4 112MB
  29. 4 - Project #2 - Medical Insurance Premium Prediction/42 - Coding Task #8 - Deploy Trained Model and Invoke Endpoint.mp4 111MB
  30. 2 - Introduction to AI_ML, AWS and Cloud Computing/07 - Introduction to AI, Machine Learning and Deep Learning - Part #2.mp4 111MB
  31. 2 - Introduction to AI_ML, AWS and Cloud Computing/06 - Introduction to AI, Machine Learning and Deep Learning.mp4 106MB
  32. 4 - Project #2 - Medical Insurance Premium Prediction/47 - Gradient Descent Algorithm.mp4 106MB
  33. 5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/60 - Project Introduction and Notebook Instance Instantiation.mp4 105MB
  34. 6 - Project #4 - Predict Cardiovascular Disease Using PCA & XGBoost (Classification)/71 - Introduction and Project Overview.mp4 99MB
  35. 5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/70 - Coding Task #13 - Retrain the Model Using best (optimized) Hyperparameters.mp4 98MB
  36. 7 - Project #5 - Deep Learning for Traffic Sign Classification Using AWS SageMaker/86 - Project Overview and Introduction.mp4 97MB
  37. 6 - Project #4 - Predict Cardiovascular Disease Using PCA & XGBoost (Classification)/83 - Coding Task #8 - Deploy Trained PCA Model Endpoint & Envoke endpoint.mp4 94MB
  38. 3 - Project #1 - Employee Salary Predictions Using AWS SageMaker Linear Learner/27 - Coding Task #4 - Create Training and Testing Dataset.mp4 92MB
  39. 6 - Project #4 - Predict Cardiovascular Disease Using PCA & XGBoost (Classification)/80 - Coding Task #4 & #5 - Visualize Datasets & Prepare Training_Testing Data.mp4 91MB
  40. 6 - Project #4 - Predict Cardiovascular Disease Using PCA & XGBoost (Classification)/79 - Coding Task #2 & #3 - Import Data_Libraries & Perform Exploratory data analysis.mp4 89MB
  41. 2 - Introduction to AI_ML, AWS and Cloud Computing/12 - Amazon S3.mp4 89MB
  42. 3 - Project #1 - Employee Salary Predictions Using AWS SageMaker Linear Learner/24 - Coding Task #1B - Using AWS SageMaker Studio (Method #2).mp4 88MB
  43. 7 - Project #5 - Deep Learning for Traffic Sign Classification Using AWS SageMaker/91 - LeNet Network Architecture.mp4 86MB
  44. 5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/66 - Coding Task #9 - Train XGBoost Locally.mp4 85MB
  45. 4 - Project #2 - Medical Insurance Premium Prediction/34 - Regression Metrics and KPIs - RMSE, MSE, MAE, MAPE.mp4 83MB
  46. 6 - Project #4 - Predict Cardiovascular Disease Using PCA & XGBoost (Classification)/85 - Coding Task #10 - Deploy Endpoint, Make Inference @ Test Model.mp4 83MB
  47. 4 - Project #2 - Medical Insurance Premium Prediction/35 - Regression Metrics and KPIs - R2 and Adjusted R2.mp4 83MB
  48. 2 - Introduction to AI_ML, AWS and Cloud Computing/13 - Amazon EC2 and IAM.mp4 83MB
  49. 2 - Introduction to AI_ML, AWS and Cloud Computing/17 - AWS SageMaker Studio Walk-through.mp4 78MB
  50. 5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/58 - Gradient Boosted Trees - Deep Dive - Part #2.mp4 77MB
  51. 4 - Project #2 - Medical Insurance Premium Prediction/39 - Coding Task #5 - Create Training and Testing Datasets.mp4 76MB
  52. 3 - Project #1 - Employee Salary Predictions Using AWS SageMaker Linear Learner/28 - Coding Task #5 - Train a Linear Regression Model in SkLearn.mp4 74MB
  53. 5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/62 - Coding Task #4 - Merge and Manipulate DataFrame Using Pandas.mp4 74MB
  54. 5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/50 - Introduction to Case Study.mp4 73MB
  55. 2 - Introduction to AI_ML, AWS and Cloud Computing/09 - Introduction to AWS and Cloud Computing.mp4 71MB
  56. 7 - Project #5 - Deep Learning for Traffic Sign Classification Using AWS SageMaker/96 - Coding Task #6 - Deploy Trained Model Using SageMaker.mp4 70MB
  57. 4 - Project #2 - Medical Insurance Premium Prediction/43 - Artificial Neural Networks for Regression Tasks.mp4 70MB
  58. 5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/68 - Coding Task #11 - Deploy XGBoost endpoint and Make Predictions.mp4 69MB
  59. 3 - Project #1 - Employee Salary Predictions Using AWS SageMaker Linear Learner/25 - Coding Task #2 - Import Key libraries and dataset.mp4 67MB
  60. 5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/51 - Basics - What is the difference between Bias & Variance.mp4 66MB
  61. 5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/63 - Coding Task #5 - Explore Merged Datasets.mp4 63MB
  62. 3 - Project #1 - Employee Salary Predictions Using AWS SageMaker Linear Learner/29 - Coding Task #6 - Evaluate Trained Model Performance.mp4 63MB
  63. 3 - Project #1 - Employee Salary Predictions Using AWS SageMaker Linear Learner/20 - Simple Linear Regression Intuition.mp4 60MB
  64. 4 - Project #2 - Medical Insurance Premium Prediction/40 - Coding Task #6 - Train a Machine Learning Model Locally.mp4 58MB
  65. 6 - Project #4 - Predict Cardiovascular Disease Using PCA & XGBoost (Classification)/78 - Coding Task #1 - SageMaker Studio Notebook Setup.mp4 58MB
  66. 2 - Introduction to AI_ML, AWS and Cloud Computing/11 - AWS Regions and Availability Zones.mp4 58MB
  67. 7 - Project #5 - Deep Learning for Traffic Sign Classification Using AWS SageMaker/94 - Coding #3 #4 - Upload Training_Testing Data to S3.mp4 56MB
  68. 5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/59 - AWS SageMaker XGBoost Algorithm.mp4 56MB
  69. 6 - Project #4 - Predict Cardiovascular Disease Using PCA & XGBoost (Classification)/73 - XGBoost for Classification Tasks (Review Lecture).mp4 55MB
  70. 6 - Project #4 - Predict Cardiovascular Disease Using PCA & XGBoost (Classification)/74 - Confusion Matrix.mp4 53MB
  71. 3 - Project #1 - Employee Salary Predictions Using AWS SageMaker Linear Learner/21 - Least Sum of Squares.mp4 52MB
  72. 1 - Introduction, Success Tips & Best Practices and Key Learning Outcomes/03 - Course Key Tips and Best Practices.mp4 51MB
  73. 2 - Introduction to AI_ML, AWS and Cloud Computing/16 - AWS SageMaker Studio Overview.mp4 48MB
  74. 5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/55 - What is Boosting.mp4 47MB
  75. 2 - Introduction to AI_ML, AWS and Cloud Computing/08 - Good Data Vs. Bad Data.mp4 46MB
  76. 2 - Introduction to AI_ML, AWS and Cloud Computing/10 - Key Machine Learning Components and AWS Management Console Tour.mp4 42MB
  77. 6 - Project #4 - Predict Cardiovascular Disease Using PCA & XGBoost (Classification)/76 - Area Under Curve (AUC) and Receiver Operating Characteristics (ROC) Metrics.mp4 42MB
  78. 4 - Project #2 - Medical Insurance Premium Prediction/46 - How do Artificial Neural Networks Train.mp4 41MB
  79. 7 - Project #5 - Deep Learning for Traffic Sign Classification Using AWS SageMaker/90 - Confusion Matrix.mp4 40MB
  80. 2 - Introduction to AI_ML, AWS and Cloud Computing/14 - AWS SageMaker Overview.mp4 38MB
  81. 5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/56 - Decision Trees and Ensemble Learning.mp4 36MB
  82. 5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/54 - Introduction to XGBoost (Extreme Gradient Boosting) algorithm.mp4 35MB
  83. 5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/65 - Coding Task #8 - Prepare the Data To Perform Training.mp4 34MB
  84. 2 - Introduction to AI_ML, AWS and Cloud Computing/05 - AWS Free Tier Account Setup and Overview.mp4 33MB
  85. 5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/52 - Basics - L1 & L2 Regularization - Part #1.mp4 32MB
  86. 1 - Introduction, Success Tips & Best Practices and Key Learning Outcomes/01 - Course Introduction and Welcome Message.mp4 25MB
  87. 4 - Project #2 - Medical Insurance Premium Prediction/48 - Backpropagation Algorithm.mp4 23MB
  88. 3 - Project #1 - Employee Salary Predictions Using AWS SageMaker Linear Learner/19 - Project Overview.mp4 21MB
  89. 4 - Project #2 - Medical Insurance Premium Prediction/33 - Multiple Linear Regression Intuition.mp4 21MB
  90. 6 - Project #4 - Predict Cardiovascular Disease Using PCA & XGBoost (Classification)/77 - Overfitting and Under fitting Models.mp4 20MB
  91. 4 - Project #2 - Medical Insurance Premium Prediction/44 - Activation Functions - Sigmoid, RELU and Tanh.mp4 20MB
  92. 4 - Project #2 - Medical Insurance Premium Prediction/45 - Multilayer Perceptron Networks.mp4 20MB
  93. 5 - Project #3 - Retail Sales Prediction Using AWS SageMaker XGBoost (Regression)/53 - Basics - L1 & L2 Regularization - Part #2.mp4 16MB
  94. 7 - Project #5 - Deep Learning for Traffic Sign Classification Using AWS SageMaker/89 - How to Improve CNNs Performance.mp4 13MB
  95. 4 - Project #2 - Medical Insurance Premium Prediction/32 - Project Overview and Introduction.mp4 11MB
  96. 1 - Introduction, Success Tips & Best Practices and Key Learning Outcomes/02 - Updates on Udemy Reviews.mp4 6MB
  97. 7 - Project #5 - Deep Learning for Traffic Sign Classification Using AWS SageMaker/92 - Request AWS SageMaker Service Limit Increase.mp4 5MB