[FreeCourseSite.com] Udemy - A Complete Guide on TensorFlow 2.0 using Keras API番号下载_[FreeCourseSite.com] Udemy - A Complete Guide on TensorFlow 2.0 using Keras API番号下载_[FreeCourseSite.com] Udemy - A Complete Guide on TensorFlow 2.0 using Keras API下载

[FreeCourseSite.com] Udemy - A Complete Guide on TensorFlow 2.0 using Keras API

种子简介

种子名称： [FreeCourseSite.com] Udemy - A Complete Guide on TensorFlow 2.0 using Keras API
文件类型：视频
文件数目： 120个文件
文件大小： 5.12 GB
收录时间： 2022-1-16 14:30
已经下载： 3次
资源热度： 184
最近下载： 2024-7-5 14:07

下载BT种子文件

下载Torrent文件(.torrent) 立即下载

磁力链接下载

magnet:?xt=urn:btih:60e579d50a847e01c1dff98fc79f74fed928d51b&dn=[FreeCourseSite.com] Udemy - A Complete Guide on TensorFlow 2.0 using Keras API 复制链接到迅雷、QQ旋风进行下载，或者使用百度云离线下载。

喜欢这个种子的人也喜欢

FreeCourseSite com Udemy - A Complete Guide on TensorFlow 2 0 using Keras API

种子包含的文件

[FreeCourseSite.com] Udemy - A Complete Guide on TensorFlow 2.0 using Keras API.torrent

1. Introduction/1. Welcome to the TensorFlow 2.0 course! Discover its structure and the TF toolkit..mp4146.28MB

10. Dataset Preprocessing with TensorFlow Transform (TFT)/1. Project Setup.mp410.06MB

10. Dataset Preprocessing with TensorFlow Transform (TFT)/2. Initial dataset preprocessing.mp434.98MB

10. Dataset Preprocessing with TensorFlow Transform (TFT)/3. Dataset metadata.mp420.93MB

10. Dataset Preprocessing with TensorFlow Transform (TFT)/4. Preprocessing function.mp421.12MB

10. Dataset Preprocessing with TensorFlow Transform (TFT)/5. Dataset preprocessing pipeline.mp473.97MB

11. Fashion API with Flask and TensorFlow 2.0/1. Project Setup.mp436.74MB

11. Fashion API with Flask and TensorFlow 2.0/2. Importing project dependencies.mp411.9MB

11. Fashion API with Flask and TensorFlow 2.0/3. Loading a pre-trained model.mp420.48MB

11. Fashion API with Flask and TensorFlow 2.0/4. Defining the Flask application.mp412.37MB

11. Fashion API with Flask and TensorFlow 2.0/5. Creating classify function.mp453.14MB

11. Fashion API with Flask and TensorFlow 2.0/6. Starting the Flask application.mp427.63MB

11. Fashion API with Flask and TensorFlow 2.0/7. Sending API requests over internet to the model.mp435.02MB

12. Image Classification API with TensorFlow Serving/1. What is the TensorFlow Serving.mp424.47MB

12. Image Classification API with TensorFlow Serving/10. Sending the POST request to a specific model.mp49.65MB

12. Image Classification API with TensorFlow Serving/2. TensorFlow Serving architecture.mp419.51MB

12. Image Classification API with TensorFlow Serving/3. Project setup.mp425.52MB

12. Image Classification API with TensorFlow Serving/4. Dataset preprocessing.mp423.71MB

12. Image Classification API with TensorFlow Serving/5. Defining, training and evaluating a model.mp423.33MB

12. Image Classification API with TensorFlow Serving/6. Saving the model for production.mp425.44MB

12. Image Classification API with TensorFlow Serving/7. Serving the TensorFlow 2.0 Model.mp427.9MB

12. Image Classification API with TensorFlow Serving/8. Creating a JSON object.mp423.58MB

12. Image Classification API with TensorFlow Serving/9. Sending the first POST request to the model.mp427.32MB

13. TensorFlow Lite Prepare a model for a mobile device/1. What is the TensorFlow Lite.mp413.96MB

13. TensorFlow Lite Prepare a model for a mobile device/2. Project setup.mp48.05MB

13. TensorFlow Lite Prepare a model for a mobile device/3. Dataset preprocessing.mp428.77MB

13. TensorFlow Lite Prepare a model for a mobile device/4. Building a model.mp414.85MB

13. TensorFlow Lite Prepare a model for a mobile device/5. Training, evaluating the model.mp415.19MB

13. TensorFlow Lite Prepare a model for a mobile device/6. Saving the model.mp49.4MB

13. TensorFlow Lite Prepare a model for a mobile device/7. TensorFlow Lite Converter.mp46.28MB

13. TensorFlow Lite Prepare a model for a mobile device/8. Converting the model to a TensorFlow Lite model.mp44.92MB

13. TensorFlow Lite Prepare a model for a mobile device/9. Saving the converted model.mp48.68MB

14. Distributed Training with TensorFlow 2.0/1. What is the Distributed Training.mp411.09MB

14. Distributed Training with TensorFlow 2.0/2. Project Setup.mp49.08MB

14. Distributed Training with TensorFlow 2.0/3. Dataset preprocessing.mp425.58MB

14. Distributed Training with TensorFlow 2.0/4. Defining a non-distributed model (normal CNN model).mp414.04MB

14. Distributed Training with TensorFlow 2.0/5. Setting up a distributed strategy.mp47.39MB

14. Distributed Training with TensorFlow 2.0/6. Defining a distributed model.mp412.49MB

14. Distributed Training with TensorFlow 2.0/7. Final evaluation - Speed test normal model vs distributed model.mp428.41MB

15. Annex 1 - Artificial Neural Networks Theory/1. Plan of Attack.mp411.84MB

15. Annex 1 - Artificial Neural Networks Theory/2. The Neuron.mp498.68MB

15. Annex 1 - Artificial Neural Networks Theory/3. The Activation Function.mp445.34MB

15. Annex 1 - Artificial Neural Networks Theory/4. How do Neural Networks Work.mp481.81MB

15. Annex 1 - Artificial Neural Networks Theory/5. How do Neural Networks Learn.mp4112.16MB

15. Annex 1 - Artificial Neural Networks Theory/6. Gradient Descent.mp460.56MB

15. Annex 1 - Artificial Neural Networks Theory/7. Stochastic Gradient Descent.mp467.24MB

15. Annex 1 - Artificial Neural Networks Theory/8. Backpropagation.mp443.12MB

16. Annex 2 - Convolutional Neural Networks Theory/1. Plan of Attack.mp415.79MB

16. Annex 2 - Convolutional Neural Networks Theory/2. What are Convolutional Neural Networks.mp4107.88MB

16. Annex 2 - Convolutional Neural Networks Theory/3. Step 1 - Convolution.mp497.84MB

16. Annex 2 - Convolutional Neural Networks Theory/4. Step 1 Bis - ReLU Layer.mp453.37MB

16. Annex 2 - Convolutional Neural Networks Theory/5. Step 2 - Max Pooling.mp4140.21MB

16. Annex 2 - Convolutional Neural Networks Theory/6. Step 3 - Flattening.mp47.92MB

16. Annex 2 - Convolutional Neural Networks Theory/7. Step 4 - Full Connection.mp4194.15MB

16. Annex 2 - Convolutional Neural Networks Theory/8. Summary.mp430.32MB

16. Annex 2 - Convolutional Neural Networks Theory/9. Softmax & Cross-Entropy.mp4117.84MB

17. Annex 3 - Recurrent Neural Networks Theory/1. Plan of Attack.mp410.48MB

17. Annex 3 - Recurrent Neural Networks Theory/2. What are Recurrent Neural Networks.mp4120.95MB

17. Annex 3 - Recurrent Neural Networks Theory/3. Vanishing Gradient.mp4111MB

17. Annex 3 - Recurrent Neural Networks Theory/4. LSTMs.mp4136.43MB

17. Annex 3 - Recurrent Neural Networks Theory/5. LSTM Practical Intuition.mp4187.42MB

17. Annex 3 - Recurrent Neural Networks Theory/6. LSTM Variations.mp420.14MB

2. TensorFlow 2.0 Basics/1. From TensorFlow 1.x to TensorFlow 2.0.mp4114.8MB

2. TensorFlow 2.0 Basics/2. Constants, Variables, Tensors.mp471.33MB

2. TensorFlow 2.0 Basics/3. Operations with Tensors.mp449.25MB

2. TensorFlow 2.0 Basics/4. Strings.mp440.23MB

3. Artificial Neural Networks/1. Project Setup.mp459.25MB

3. Artificial Neural Networks/2. Data Preprocessing.mp461.76MB

3. Artificial Neural Networks/3. Building the Artificial Neural Network.mp460.43MB

3. Artificial Neural Networks/4. Training the Artificial Neural Network.mp448.51MB

3. Artificial Neural Networks/5. Evaluating the Artificial Neural Network.mp431.44MB

4. Convolutional Neural Networks/1. Project Setup & Data Preprocessing.mp447.36MB

4. Convolutional Neural Networks/2. Building the Convolutional Neural Network.mp488.18MB

4. Convolutional Neural Networks/3. Training and Evaluating the Convolutional Neural Network.mp458.24MB

5. Recurrent Neural Networks/1. Project Setup & Data Preprocessing.mp446.44MB

5. Recurrent Neural Networks/2. Building the Recurrent Neural Network.mp440.03MB

5. Recurrent Neural Networks/3. Training and Evaluating the Recurrent Neural Network.mp448.88MB

6. Transfer Learning and Fine Tuning/1. What is Transfer Learning.mp446.49MB

6. Transfer Learning and Fine Tuning/10. Transfer Learning.mp416.82MB

6. Transfer Learning and Fine Tuning/11. Evaluating Transfer Learning results.mp49.37MB

6. Transfer Learning and Fine Tuning/12. Fine Tuning model definition.mp424.59MB

6. Transfer Learning and Fine Tuning/13. Compiling the Fine Tuning model.mp46.41MB

6. Transfer Learning and Fine Tuning/14. Fine Tuning.mp410.17MB

6. Transfer Learning and Fine Tuning/15. Evaluating Fine Tuning results.mp49MB

6. Transfer Learning and Fine Tuning/2. Project Setup.mp449.37MB

6. Transfer Learning and Fine Tuning/3. Dataset preprocessing.mp431.84MB

6. Transfer Learning and Fine Tuning/4. Loading the MobileNet V2 model.mp417.83MB

6. Transfer Learning and Fine Tuning/5. Freezing the pre-trained model.mp46.08MB

6. Transfer Learning and Fine Tuning/6. Adding a custom head to the pre-trained model.mp419.69MB

6. Transfer Learning and Fine Tuning/7. Defining the transfer learning model.mp413.19MB

6. Transfer Learning and Fine Tuning/8. Compiling the Transfer Learning model.mp412.58MB

6. Transfer Learning and Fine Tuning/9. Image Data Generators.mp432.56MB

7. Deep Reinforcement Learning Theory/1. What is Reinforcement Learning.mp468.55MB

7. Deep Reinforcement Learning Theory/2. The Bellman Equation.mp495.05MB

7. Deep Reinforcement Learning Theory/3. Markov Decision Process (MDP).mp494.29MB

7. Deep Reinforcement Learning Theory/4. Q-Learning Intuition.mp479.08MB

7. Deep Reinforcement Learning Theory/5. Temporal Difference.mp497.1MB

7. Deep Reinforcement Learning Theory/6. Deep Q-Learning Intuition - Step 1.mp499.93MB

7. Deep Reinforcement Learning Theory/7. Deep Q-Learning Intuition - Step 2.mp443.07MB

7. Deep Reinforcement Learning Theory/8. Experience Replay.mp4114.74MB

7. Deep Reinforcement Learning Theory/9. Action Selection Policies.mp4136.84MB

8. Deep Reinforcement Learning for Stock Market trading/1. Project Setup.mp411.9MB

8. Deep Reinforcement Learning for Stock Market trading/10. Defining the model.mp411.86MB

8. Deep Reinforcement Learning for Stock Market trading/11. Training loop - Step 1.mp428.12MB

8. Deep Reinforcement Learning for Stock Market trading/12. Training loop - Step 2.mp454.19MB

8. Deep Reinforcement Learning for Stock Market trading/2. AI Trader - Step 1.mp427.2MB

8. Deep Reinforcement Learning for Stock Market trading/3. AI Trader - Step 2.mp411.9MB

8. Deep Reinforcement Learning for Stock Market trading/4. AI Trader - Step 3.mp415.84MB

8. Deep Reinforcement Learning for Stock Market trading/5. AI Trader - Step 4.mp415.92MB

8. Deep Reinforcement Learning for Stock Market trading/6. AI Trader - Step 5.mp433.19MB

8. Deep Reinforcement Learning for Stock Market trading/7. Dataset Loader function.mp438.88MB

8. Deep Reinforcement Learning for Stock Market trading/8. State creator function.mp432.32MB

8. Deep Reinforcement Learning for Stock Market trading/9. Loading the dataset.mp410.04MB

9. Data Validation with TensorFlow Data Validation (TFDV)/1. Project Setup.mp422.28MB

9. Data Validation with TensorFlow Data Validation (TFDV)/2. Loading the pollution dataset.mp424.84MB

9. Data Validation with TensorFlow Data Validation (TFDV)/3. Creating dataset Schema.mp424.1MB

9. Data Validation with TensorFlow Data Validation (TFDV)/4. Computing test set statistics.mp42.46MB

9. Data Validation with TensorFlow Data Validation (TFDV)/5. Anomaly detection with TensorFlow Data Validation.mp423.95MB

9. Data Validation with TensorFlow Data Validation (TFDV)/6. Preparing Schema for production.mp419.72MB

9. Data Validation with TensorFlow Data Validation (TFDV)/7. Saving the Schema.mp48.1MB