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ZerotoMastery AI Engineering Bootcamp Build Train and Deploy Models with AWS SageMaker

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ZerotoMastery AI for Beginners Inside Large Language Models DevCourse… ZerotoMastery AI for Beginners Inside Large Language Models DevCourseWeb
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ZerotoMastery AI Engineering Bootcamp Build Train and Deploy Models w… ZerotoMastery AI Engineering Bootcamp Build Train and Deploy Models with AWS SageMaker
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Files:
  1. Get Bonus Downloads Here.url 182 bytes
  2. 01. AI Engineering Bootcamp Learn AWS SageMaker with Patrik Szepesi - Zer - 1920x1080 2055K.mp4 17.1 MB
  3. 02. Course Introduction - Zer - 1920x1080 278K.mp4 17.4 MB
  4. 03. Setting Up Our AWS Account - Zer - 1920x1080 441K.mp4 13.0 MB
  5. 04. Set Up IAM Roles + Best Practices - Zer - 1920x1080 484K.mp4 23.3 MB
  6. 05. AWS Security Best Practices - Zer - 1920x1080 468K.mp4 22.0 MB
  7. 06. Set Up AWS SageMaker Domain - Zer - 1920x1080 453K.mp4 6.5 MB
  8. 07. UI Domain Change - Zer - 1920x1080 606K.mp4 2.5 MB
  9. 08. Setting Up SageMaker Environment - Zer - 1920x1080 416K.mp4 13.2 MB
  10. 09. SageMaker Studio and Pricing - Zer - 1920x1080 429K.mp4 28.4 MB
  11. 10. Setup SageMaker Server + PyTorch - Zer - 1920x1080 342K.mp4 15.8 MB
  12. 11. HuggingFace Models, Sentiment Analysis, and AutoScaling - Zer - 1920x1080 703K.mp4 91.8 MB
  13. 12. Get Dataset for Multiclass Text Classification - Zer - 1920x1080 337K.mp4 14.9 MB
  14. 13. Creating Our AWS S3 Bucket - Zer - 1920x1080 445K.mp4 12.1 MB
  15. 14. Uploading Our Training Data to S3 - Zer - 1920x1080 497K.mp4 4.6 MB
  16. 15. Exploratory Data Analysis - Part 1 - Zer - 1920x1080 422K.mp4 40.0 MB
  17. 16. Exploratory Data Analysis - Part 2 - Zer - 1920x1080 323K.mp4 13.8 MB
  18. 17. Data Visualization and Best Practices - Zer - 1920x1080 296K.mp4 26.0 MB
  19. 18. Setting Up Our Training Job Notebook + Reasons to Use SageMaker - Zer - 1920x1080 457K.mp4 55.7 MB
  20. 19. Python Script for HuggingFace Estimator - Zer - 1920x1080 254K.mp4 28.2 MB
  21. 20. Creating Our Optional Experiment Notebook - Part 1 - Zer - 1920x1080 441K.mp4 9.7 MB
  22. 21. Creating Our Optional Experiment Notebook - Part 2 - Zer - 1920x1080 747K.mp4 18.6 MB
  23. 22. Encoding Categorical Labels to Numeric Values - Zer - 1920x1080 453K.mp4 39.9 MB
  24. 23. Understanding the Tokenization Vocabulary - Zer - 1920x1080 286K.mp4 30.1 MB
  25. 24. Encoding Tokens - Zer - 1920x1080 318K.mp4 25.2 MB
  26. 25. Practical Example of Tokenization and Encoding - Zer - 1920x1080 395K.mp4 32.7 MB
  27. 26. Creating Our Dataset Loader Class - Zer - 1920x1080 390K.mp4 44.6 MB
  28. 27. Setting Pytorch DataLoader - Zer - 1920x1080 337K.mp4 36.7 MB
  29. 28. Which Path Will You Take_ - Zer - 1920x1080 227K.mp4 2.4 MB
  30. 29. DistilBert vs. Bert Differences - Zer - 1920x1080 234K.mp4 7.7 MB
  31. 30. Embeddings In A Continuous Vector Space - Zer - 1920x1080 240K.mp4 12.9 MB
  32. 31. Introduction To Positional Encodings - Zer - 1920x1080 229K.mp4 8.3 MB
  33. 32. Positional Encodings - Part 1 - Zer - 1920x1080 384K.mp4 10.1 MB
  34. 33. Positional Encodings - Part 2 (Even and Odd Indices) - Zer - 1920x1080 297K.mp4 20.9 MB
  35. 34. Why Use Sine and Cosine Functions - Zer - 1920x1080 337K.mp4 12.2 MB
  36. 35. Understanding the Nature of Sine and Cosine Functions - Zer - 1920x1080 419K.mp4 26.9 MB
  37. 36. Visualizing Positional Encodings in Sine and Cosine Graphs - Zer - 1920x1080 404K.mp4 25.2 MB
  38. 37. Solving the Equations to Get the Values for Positional Encodings - Zer - 1920x1080 324K.mp4 39.2 MB
  39. 38. Introduction to Attention Mechanism - Zer - 1920x1080 245K.mp4 5.2 MB
  40. 39. Query, Key and Value Matrix - Zer - 1920x1080 236K.mp4 29.6 MB
  41. 40. Getting Started with Our Step by Step Attention Calculation - Zer - 1920x1080 249K.mp4 13.0 MB
  42. 41. Calculating Key Vectors - Zer - 1920x1080 349K.mp4 52.3 MB
  43. 42. Query Matrix Introduction - Zer - 1920x1080 293K.mp4 23.7 MB
  44. 43. Calculating Raw Attention Scores - Zer - 1920x1080 295K.mp4 48.0 MB
  45. 44. Understanding the Mathematics Behind Dot Products and Vector Alignment - Zer - 1920x1080 328K.mp4 31.5 MB
  46. 45. Visualizing Raw Attention Scores in 2D - Zer - 1920x1080 310K.mp4 13.0 MB
  47. 46. Converting Raw Attention Scores to Probability Distributions with Softmax - Zer - 1920x1080 379K.mp4 24.0 MB
  48. 47. Normalization - Zer - 1920x1080 304K.mp4 7.6 MB
  49. 48. Understanding the Value Matrix and Value Vector - Zer - 1920x1080 296K.mp4 21.3 MB
  50. 49. Calculating the Final Context Aware Rich Representation for the Word _River_ - Zer - 1920x1080 430K.mp4 33.7 MB
  51. 50. Understanding the Output - Zer - 1920x1080 497K.mp4 5.4 MB
  52. 51. Understanding Multi Head Attention - Zer - 1920x1080 345K.mp4 30.0 MB
  53. 52. Multi Head Attention Example and Subsequent Layers - Zer - 1920x1080 446K.mp4 33.1 MB
  54. 53. Masked Language Learning - Zer - 1920x1080 164K.mp4 3.2 MB
  55. 54. Exercise Imposter Syndrome - Zer - 1920x1080 894K.mp4 10.5 MB
  56. 55. Creating Our Custom Model Architecture with PyTorch - Zer - 1920x1080 293K.mp4 37.2 MB
  57. 56. Adding the Dropout, Linear Layer, and ReLU to Our Model - Zer - 1920x1080 317K.mp4 33.4 MB
  58. 57. Creating Our Accuracy Function - Zer - 1920x1080 296K.mp4 28.0 MB
  59. 58. Creating Our Train Function - Zer - 1920x1080 355K.mp4 47.6 MB
  60. 59. Finishing Our Train Function - Zer - 1920x1080 367K.mp4 20.5 MB
  61. 60. Setting Up the Validation Function - Zer - 1920x1080 354K.mp4 34.9 MB
  62. 61. Passing Parameters In SageMaker - Zer - 1920x1080 416K.mp4 11.4 MB
  63. 62. Setting Up Model Parameters For Training - Zer - 1920x1080 296K.mp4 9.9 MB
  64. 63. Understanding The Mathematics Behind Cross Entropy Loss - Zer - 1920x1080 359K.mp4 13.7 MB
  65. 64. Finishing Our Script.py File - Zer - 1920x1080 412K.mp4 20.8 MB
  66. 65. Quota Increase - Zer - 1920x1080 549K.mp4 24.8 MB
  67. 66. Starting Our Training Job - Zer - 1920x1080 863K.mp4 44.5 MB
  68. 67. Debugging Our Training Job With AWS CloudWatch - Zer - 1920x1080 606K.mp4 58.1 MB
  69. 68. Analyzing Our Training Job Results - Zer - 1920x1080 707K.mp4 29.7 MB
  70. 69. Creating Our Inference Script For Our PyTorch Model - Zer - 1920x1080 324K.mp4 19.5 MB
  71. 70. Finishing Our PyTorch Inference Script - Zer - 1920x1080 365K.mp4 23.4 MB
  72. 71. Setting Up Our Deployment - Zer - 1920x1080 476K.mp4 26.0 MB
  73. 72. Deploying Our Model To A SageMaker Endpoint - Zer - 1920x1080 631K.mp4 36.2 MB
  74. 73. Introduction to Endpoint Load Testing - Zero To Mastery Academy - 1920x1080 213K.mp4 7.9 MB
  75. 74. Creating Our Test Data for Load Testing - Zero To Mastery Academy - 1920x1080 230K.mp4 18.5 MB
  76. 75. Upload Testing Data to S3 - Zero To Mastery Academy - 1920x1080 715K.mp4 4.5 MB
  77. 76. Creating Our Model for Load Testing - Zero To Mastery Academy - 1920x1080 782K.mp4 18.8 MB
  78. 77. Starting Our Load Test Job - Zero To Mastery Academy - 1920x1080 621K.mp4 27.5 MB
  79. 78. Analyze Load Test Results - Zero To Mastery Academy - 1920x1080 425K.mp4 28.2 MB
  80. 79. Deploying Our Endpoint - Zero To Mastery Academy - 1920x1080 538K.mp4 14.4 MB
  81. 80. Creating Lambda Function to Call Our Endpoint - Zero To Mastery Academy - 1920x1080 412K.mp4 28.2 MB
  82. 81. Setting Up Our AWS API Gateway - Zero To Mastery Academy - 1920x1080 449K.mp4 15.9 MB
  83. 82. Testing Our Model with Postman, API Gateway and Lambda - Zero To Mastery Academy - 1920x1080 518K.mp4 20.0 MB
  84. 83. Cleaning Up Resources - Zero To Mastery Academy - 1920x1080 421K.mp4 8.3 MB
  85. 84. Thank You! - Zero To Mastery Academy - 1920x1080 1046K.mp4 4.3 MB
  86. AI Engineering Bootcamp Build, Train & Deploy Models with AWS SageMaker.txt 3.3 KB
  87. Bonus Resources.txt 386 bytes

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