Accelerating TensorFlow with the Google Machine Learning Engine
| 文件类型 | 收录时间 | 最后活跃 | 资源热度 | 文件大小 | 文件数量 |
|---|---|---|---|---|---|
| 视频 | 2021-10-24 18:19 | 2024-10-27 22:20 | 225 | 340.01 MB | 42 |
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文件列表
- 3.3. Training TensorFlow Applications/18.Linear regression in code - Part 2.mp422.14MB
- 0.Introduction/01.Welcome.mp44.87MB
- 0.Introduction/02.What you should know.mp42.64MB
- 0.Introduction/03.Using the exercise files.mp42.12MB
- 1.1. Introducing TensorFlow/04.Overview and installation.mp45.19MB
- 1.1. Introducing TensorFlow/05.Getting started.mp43.67MB
- 1.1. Introducing TensorFlow/06.Running a simple application.mp45.92MB
- 2.2. Fundamentals of TensorFlow Development/07.Creating tensors.mp46.23MB
- 2.2. Fundamentals of TensorFlow Development/08.Basic tensor operations.mp44.28MB
- 2.2. Fundamentals of TensorFlow Development/09.Advanced tensor operations.mp44.14MB
- 2.2. Fundamentals of TensorFlow Development/10.Understanding graphs and sessions.mp45.12MB
- 2.2. Fundamentals of TensorFlow Development/11.Accessing graphs and sessions in code.mp49.42MB
- 3.3. Training TensorFlow Applications/12.Variables and logging.mp47.16MB
- 3.3. Training TensorFlow Applications/13.Using variables in code.mp45.94MB
- 3.3. Training TensorFlow Applications/14.Using optimizers.mp49.73MB
- 3.3. Training TensorFlow Applications/15.Simple optimizer example.mp410.04MB
- 3.3. Training TensorFlow Applications/16.Batches and placeholders.mp45.37MB
- 3.3. Training TensorFlow Applications/17.Linear regression in code - Part 1.mp46.12MB
- 3.3. Training TensorFlow Applications/19.TensorBoard.mp45.28MB
- 3.3. Training TensorFlow Applications/20.Using TensorBoard in practice.mp413.05MB
- 4.4. Accessing Data with Datasets/21.Datasets and iterators.mp48.7MB
- 4.4. Accessing Data with Datasets/22.Coding with datasets and iterators.mp412.35MB
- 4.4. Accessing Data with Datasets/23.Dataset operations.mp47.61MB
- 4.4. Accessing Data with Datasets/24.Creating datasets from files.mp48.27MB
- 4.4. Accessing Data with Datasets/25.Introducing MNIST images.mp45.42MB
- 4.4. Accessing Data with Datasets/26.Reading MNIST data in code.mp414.41MB
- 5.5. Machine Learning with Estimators/27.Understanding estimators.mp48.49MB
- 5.5. Machine Learning with Estimators/28.Describing data with feature columns.mp49.37MB
- 5.5. Machine Learning with Estimators/29.Coding a simple estimator - Part 1.mp47.06MB
- 5.5. Machine Learning with Estimators/30.Coding a simple estimator - Part 2.mp410.5MB
- 5.5. Machine Learning with Estimators/31.Estimators and neural networks.mp46.17MB
- 5.5. Machine Learning with Estimators/32.Coding a DNN estimator - Part 1.mp415.37MB
- 5.5. Machine Learning with Estimators/33.Coding a DNN estimator - Part 2.mp416.92MB
- 5.5. Machine Learning with Estimators/34.Automating estimator operation.mp45.42MB
- 5.5. Machine Learning with Estimators/35.Estimator automation in practice.mp415.87MB
- 6.6. Deploying Estimators to the Machine Learning Engine/36.Creating a GCP project.mp49.1MB
- 6.6. Deploying Estimators to the Machine Learning Engine/37.Installing the Cloud SDK.mp48.39MB
- 6.6. Deploying Estimators to the Machine Learning Engine/38.Introduction to Google Cloud Storage.mp44.58MB
- 6.6. Deploying Estimators to the Machine Learning Engine/39.Accessing Cloud Storage in practice.mp45.93MB
- 6.6. Deploying Estimators to the Machine Learning Engine/40.Machine Learning Engine.mp46.11MB
- 6.6. Deploying Estimators to the Machine Learning Engine/41.Deploying jobs to ML Engine.mp412.1MB
- 7.Conclusion/42.Next steps.mp43.44MB
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