[ WebToolTip com ] Udemy - Production-Grade Deep Learning Pipelines
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| Torrent Hash : | 2BF58F49FF96C64922B149109225A68F57CCD1D1 |
| Torrent Added : | 16 days ago in Other - Other |
| Torrent Size : | 3.13 GB |
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Torrent File Content (411 files)
[ WebToolTip.com ] Udemy - Production-Grade Deep Learning Pipelines
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180 bytes
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1 - Lesson 1.1 - Welcome and Course Roadmap/1. Module Overview - Introduction & Local Setup.mp4 -
1 - Lesson 1.1 - Welcome and Course Roadmap/1. Module Overview - Introduction & Local Setup.mp4 -
3.81 MB
1 - Lesson 1.1 - Welcome and Course Roadmap/2. Lesson 1.1 - Welcome and Course Roadmap.mp4 -
1.67 MB
1 - Lesson 1.1 - Welcome and Course Roadmap/3. What Problem Does This Course Solve.mp4 -
2.67 MB
1 - Lesson 1.1 - Welcome and Course Roadmap/4. What You Will Build.mp4 -
2.62 MB
1 - Lesson 1.1 - Welcome and Course Roadmap/5. Course Structure.mp4 -
2.72 MB
1 - Lesson 1.1 - Welcome and Course Roadmap/6. Prerequisites.mp4 -
1.98 MB
10 - Lesson 3.1 – DNN Architecture - Design and Build/64. Module Overview - Local Model Development & Experimentation.mp4 -
4.61 MB
10 - Lesson 3.1 – DNN Architecture - Design and Build/65. Lesson 3.1 - DNN Architecture - Design and Build.mp4 -
7.07 MB
10 - Lesson 3.1 – DNN Architecture - Design and Build/66. Sequential vs. Functional API.mp4 -
4.09 MB
10 - Lesson 3.1 – DNN Architecture - Design and Build/67. The Three Layer Building Blocks.mp4 -
5.16 MB
10 - Lesson 3.1 – DNN Architecture - Design and Build/68. The create_dnn_model Function.mp4 -
5.68 MB
10 - Lesson 3.1 – DNN Architecture - Design and Build/69. Output Layer Design for Regression.mp4 -
2.82 MB
10 - Lesson 3.1 – DNN Architecture - Design and Build/70. Note on Kernel Regularizer.mp4 -
4.36 MB
10 - Lesson 3.1 – DNN Architecture - Design and Build/71. Architecture Concepts.mp4 -
5.87 MB
11 - Lesson 3.2 – Compiling, Callbacks, and Training/72. Lesson 3.2 - Compiling, Callbacks, and Training.mp4 -
2.42 MB
11 - Lesson 3.2 – Compiling, Callbacks, and Training/73. Compilation.mp4 -
5.27 MB
11 - Lesson 3.2 – Compiling, Callbacks, and Training/74. Early Stopping.mp4 -
3.1 MB
11 - Lesson 3.2 – Compiling, Callbacks, and Training/75. Reduce Learning Rate on Plateau.mp4 -
3.07 MB
11 - Lesson 3.2 – Compiling, Callbacks, and Training/76. The train_dnn_model Function.mp4 -
2.15 MB
11 - Lesson 3.2 – Compiling, Callbacks, and Training/77. Dataset Shuffle.mp4 -
2.66 MB
12 - Lesson 3.3 – MLflow Experiment Tracking/78. Lesson 3.3 - MLflow Experiment Tracking.mp4 -
5.42 MB
12 - Lesson 3.3 – MLflow Experiment Tracking/79. The Problem MLflow Solves.mp4 -
3.09 MB
12 - Lesson 3.3 – MLflow Experiment Tracking/80. MLflow Core Concepts.mp4 -
4.99 MB
12 - Lesson 3.3 – MLflow Experiment Tracking/81. Running the MLflow Server.mp4 -
2.16 MB
12 - Lesson 3.3 – MLflow Experiment Tracking/82. The train_dnn_model Function Logs.mp4 -
3.64 MB
13 - Lesson 3.4 – Evaluation, Visualization, and Model Serving/3. Quiz 3.html -
25.56 KB
13 - Lesson 3.4 – Evaluation, Visualization, and Model Serving/83. Lesson 3.4 - Evaluation, Visualization, and Model Serving.mp4 -
3.26 MB
13 - Lesson 3.4 – Evaluation, Visualization, and Model Serving/84. Evaluating on the Test Set.mp4 -
4.81 MB
13 - Lesson 3.4 – Evaluation, Visualization, and Model Serving/85. R Squared.mp4 -
2.11 MB
13 - Lesson 3.4 – Evaluation, Visualization, and Model Serving/86. Learning Curves.mp4 -
4.51 MB
13 - Lesson 3.4 – Evaluation, Visualization, and Model Serving/87. The plot_metric Function.mp4 -
2.32 MB
13 - Lesson 3.4 – Evaluation, Visualization, and Model Serving/88. model.save() and the SavedModel Format.mp4 -
4.28 MB
13 - Lesson 3.4 – Evaluation, Visualization, and Model Serving/89. 3_model_arch.ipynb.bin -
132.48 KB
13 - Lesson 3.4 – Evaluation, Visualization, and Model Serving/89. Lab - Loading and Preprocessing the Data.mp4 -
23.93 MB
13 - Lesson 3.4 – Evaluation, Visualization, and Model Serving/90. Lab - Building, Training, and Tracking the DNN with MLflow.mp4 -
111 MB
14 - Lesson 4.1 – TFX - From Scripts to Pipelines/01_experimentation/1_data_ingest.ipynb -
4.79 KB
14 - Lesson 4.1 – TFX - From Scripts to Pipelines/01_experimentation/2_feature_eng.ipynb -
220.28 KB
14 - Lesson 4.1 – TFX - From Scripts to Pipelines/01_experimentation/3_model_arch.ipynb -
132.48 KB
14 - Lesson 4.1 – TFX - From Scripts to Pipelines/01_experimentation/4_tfx_pipeline.ipynb -
540.65 KB
14 - Lesson 4.1 – TFX - From Scripts to Pipelines/01_experimentation/module.py -
13.21 KB
14 - Lesson 4.1 – TFX - From Scripts to Pipelines/100. Lab - TFX Notebook Introduction.mp4 -
2.97 MB
14 - Lesson 4.1 – TFX - From Scripts to Pipelines/101. Lab - TFX Imports and Libraries.mp4 -
37.49 MB
14 - Lesson 4.1 – TFX - From Scripts to Pipelines/102. Lab - Pipeline Data Directory.mp4 -
8.62 MB
14 - Lesson 4.1 – TFX - From Scripts to Pipelines/91. Module Overview - Introducing TFX.mp4 -
5.84 MB
14 - Lesson 4.1 – TFX - From Scripts to Pipelines/92. Lesson 4.1 - TFX - From Scripts to Pipelines.mp4 -
3.09 MB
14 - Lesson 4.1 – TFX - From Scripts to Pipelines/93. The Problem Modules 2 and 3 Left Unsolved.mp4 -
4.44 MB
14 - Lesson 4.1 – TFX - From Scripts to Pipelines/94. What TFX Is.mp4 -
3.32 MB
14 - Lesson 4.1 – TFX - From Scripts to Pipelines/95. Three Foundational TFX Concepts.mp4 -
5.94 MB
14 - Lesson 4.1 – TFX - From Scripts to Pipelines/96. The Interactive Context.mp4 -
+ Show all torrent content...4.63 MB
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