[DesireCourse.Net] Udemy - Tensorflow 2.0 Deep Learning and Artificial Intelligence - 磁力管家

BT种子名称

分享给好友

BT种子基本信息

种子哈希：60dca90d26f7e9e3f24f04a2fc6dd22af9b6fb1f
文档大小：7.6 GB
文档个数：262个文档
下载次数：457次
下载速度：极快
收录时间：2021-04-13
最近下载：2025-03-31
DMCA/屏蔽：DMCA/屏蔽

下载磁力链接

magnet:?xt=urn:btih:60DCA90D26F7E9E3F24F04A2FC6DD22AF9B6FB1F
复制磁力链接到utorrent、Bitcomet、迅雷、115、百度网盘等下载工具进行下载。

下载BT种子

磁力链接种子下载迅雷下载二维码迅雷看看
磁力链接在线播放？试试百度云网盘离线下载播放！

[DesireCourse.Net] Udemy - Tensorflow 2.0 Deep Learning and Artificial Intelligence的二维码

文档列表

18. Setting up your Environment/2. Windows-Focused Environment Setup 2018.mp4 203.4 MB
18. Setting up your Environment/3. Installing NVIDIA GPU-Accelerated Deep Learning Libraries on your Home Computer.mp4 175.4 MB
18. Setting up your Environment/1. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 174.8 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/12. Demo of the Long Distance Problem.mp4 150.1 MB
13. Advanced Tensorflow Usage/2. Tensorflow Serving pt 2.mp4 130.5 MB
20. Effective Learning Strategies for Machine Learning/4. What order should I take your courses in (part 2).mp4 128.6 MB
20. Effective Learning Strategies for Machine Learning/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 122.8 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/1. Sequence Data.mp4 108.2 MB
11. Deep Reinforcement Learning (Theory)/2. Elements of a Reinforcement Learning Problem.mp4 102.5 MB
4. Feedforward Artificial Neural Networks/4. Activation Functions.mp4 96.7 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/5. Recurrent Neural Networks.mp4 96.5 MB
5. Convolutional Neural Networks/5. CNN Architecture.mp4 95.4 MB
2. Google Colab/3. Uploading your own data to Google Colab.mp4 93.4 MB
20. Effective Learning Strategies for Machine Learning/3. What order should I take your courses in (part 1).mp4 92.4 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/3. Autoregressive Linear Model for Time Series Prediction.mp4 91.9 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/7. RNN for Time Series Prediction.mp4 91.5 MB
10. GANs (Generative Adversarial Networks)/1. GAN Theory.mp4 90.7 MB
5. Convolutional Neural Networks/11. Improving CIFAR-10 Results.mp4 90.6 MB
5. Convolutional Neural Networks/6. CNN Code Preparation.mp4 90.5 MB
4. Feedforward Artificial Neural Networks/9. ANN for Regression.mp4 88.0 MB
12. Stock Trading Project with Deep Reinforcement Learning/6. Code pt 2.mp4 87.4 MB
19. Extra Help With Python Coding for Beginners/1. How to Code Yourself (part 1).mp4 86.1 MB
4. Feedforward Artificial Neural Networks/6. How to Represent Images.mp4 84.8 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/15. Stock Return Predictions using LSTMs (pt 1).mp4 83.9 MB
5. Convolutional Neural Networks/1. What is Convolution (part 1).mp4 83.7 MB
10. GANs (Generative Adversarial Networks)/2. GAN Code.mp4 82.0 MB
19. Extra Help With Python Coding for Beginners/3. Proof that using Jupyter Notebook is the same as not using it.mp4 81.7 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/11. A More Challenging Sequence.mp4 81.4 MB
5. Convolutional Neural Networks/4. Convolution on Color Images.mp4 80.8 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/17. Stock Return Predictions using LSTMs (pt 3).mp4 80.5 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/9. GRU and LSTM (pt 1).srt 79.8 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/9. GRU and LSTM (pt 1).mp4 79.8 MB
1. Welcome/2. Outline.mp4 77.3 MB
3. Machine Learning and Neurons/1. What is Machine Learning.mp4 76.7 MB
3. Machine Learning and Neurons/6. Regression Notebook.mp4 75.2 MB
14. Low-Level Tensorflow/3. Variables and Gradient Tape.mp4 74.1 MB
14. Low-Level Tensorflow/4. Build Your Own Custom Model.mp4 73.6 MB
8. Recommender Systems/1. Recommender Systems with Deep Learning Theory.mp4 72.1 MB
3. Machine Learning and Neurons/2. Code Preparation (Classification Theory).mp4 71.8 MB
9. Transfer Learning for Computer Vision/5. Transfer Learning Code (pt 1).mp4 69.8 MB
3. Machine Learning and Neurons/4. Classification Notebook.mp4 69.5 MB
2. Google Colab/1. Intro to Google Colab, how to use a GPU or TPU for free.mp4 68.3 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/8. Paying Attention to Shapes.mp4 67.5 MB
7. Natural Language Processing (NLP)/2. Code Preparation (NLP).mp4 66.0 MB
12. Stock Trading Project with Deep Reinforcement Learning/7. Code pt 3.mp4 65.4 MB
11. Deep Reinforcement Learning (Theory)/11. Q-Learning.mp4 64.3 MB
7. Natural Language Processing (NLP)/4. Text Classification with LSTMs.mp4 63.5 MB
12. Stock Trading Project with Deep Reinforcement Learning/8. Code pt 4.mp4 62.0 MB
8. Recommender Systems/2. Recommender Systems with Deep Learning Code.mp4 61.7 MB
4. Feedforward Artificial Neural Networks/8. ANN for Image Classification.mp4 61.2 MB
7. Natural Language Processing (NLP)/1. Embeddings.mp4 60.8 MB
4. Feedforward Artificial Neural Networks/3. The Geometrical Picture.mp4 59.2 MB
19. Extra Help With Python Coding for Beginners/2. How to Code Yourself (part 2).mp4 59.2 MB
4. Feedforward Artificial Neural Networks/7. Code Preparation (ANN).mp4 58.9 MB
12. Stock Trading Project with Deep Reinforcement Learning/2. Data and Environment.mp4 58.7 MB
11. Deep Reinforcement Learning (Theory)/12. Deep Q-Learning DQN (pt 1).mp4 58.4 MB
9. Transfer Learning for Computer Vision/1. Transfer Learning Theory.mp4 57.8 MB
3. Machine Learning and Neurons/8. How does a model learn.mp4 57.7 MB
11. Deep Reinforcement Learning (Theory)/9. Solving the Bellman Equation with Reinforcement Learning (pt 2).mp4 55.1 MB
5. Convolutional Neural Networks/7. CNN for Fashion MNIST.mp4 54.2 MB
2. Google Colab/2. Tensorflow 2.0 in Google Colab.mp4 53.6 MB
13. Advanced Tensorflow Usage/4. Why is Google the King of Distributed Computing.mp4 53.3 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/10. GRU and LSTM (pt 2).mp4 52.8 MB
14. Low-Level Tensorflow/2. Constants and Basic Computation.mp4 52.7 MB
13. Advanced Tensorflow Usage/5. Training with Distributed Strategies.mp4 52.5 MB
3. Machine Learning and Neurons/7. The Neuron.mp4 51.8 MB
11. Deep Reinforcement Learning (Theory)/13. Deep Q-Learning DQN (pt 2).mp4 51.6 MB
11. Deep Reinforcement Learning (Theory)/4. Markov Decision Processes (MDPs).mp4 51.3 MB
4. Feedforward Artificial Neural Networks/5. Multiclass Classification.mp4 49.1 MB
12. Stock Trading Project with Deep Reinforcement Learning/5. Code pt 1.mp4 49.1 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/2. Forecasting.mp4 49.0 MB
4. Feedforward Artificial Neural Networks/2. Forward Propagation.mp4 49.0 MB
7. Natural Language Processing (NLP)/6. Text Classification with CNNs.mp4 48.7 MB
9. Transfer Learning for Computer Vision/6. Transfer Learning Code (pt 2).mp4 48.3 MB
19. Extra Help With Python Coding for Beginners/4. Is Theano Dead.mp4 46.6 MB
2. Google Colab/4. Where can I learn about Numpy, Scipy, Matplotlib, Pandas, and Scikit-Learn.mp4 46.0 MB
11. Deep Reinforcement Learning (Theory)/6. Value Functions and the Bellman Equation.mp4 45.4 MB
11. Deep Reinforcement Learning (Theory)/3. States, Actions, Rewards, Policies.mp4 45.1 MB
16. In-Depth Gradient Descent/5. Adam.mp4 44.7 MB
14. Low-Level Tensorflow/1. Differences Between Tensorflow 1.x and Tensorflow 2.x.mp4 44.6 MB
13. Advanced Tensorflow Usage/3. Tensorflow Lite (TFLite).mp4 44.5 MB
3. Machine Learning and Neurons/9. Making Predictions.mp4 44.0 MB
7. Natural Language Processing (NLP)/5. CNNs for Text.mp4 42.4 MB
16. In-Depth Gradient Descent/3. Momentum.mp4 41.3 MB
5. Convolutional Neural Networks/9. Data Augmentation.mp4 41.1 MB
1. Welcome/1. Introduction.mp4 41.1 MB
11. Deep Reinforcement Learning (Theory)/8. Solving the Bellman Equation with Reinforcement Learning (pt 1).mp4 40.9 MB
20. Effective Learning Strategies for Machine Learning/1. How to Succeed in this Course (Long Version).mp4 40.8 MB
16. In-Depth Gradient Descent/4. Variable and Adaptive Learning Rates.mp4 40.4 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/16. Stock Return Predictions using LSTMs (pt 2).mp4 40.1 MB
21. Appendix FAQ/2. BONUS Where to get discount coupons and FREE deep learning material.mp4 39.7 MB
11. Deep Reinforcement Learning (Theory)/1. Deep Reinforcement Learning Section Introduction.mp4 39.6 MB
11. Deep Reinforcement Learning (Theory)/10. Epsilon-Greedy.mp4 39.4 MB
11. Deep Reinforcement Learning (Theory)/14. How to Learn Reinforcement Learning.mp4 39.3 MB
15. In-Depth Loss Functions/1. Mean Squared Error.mp4 39.2 MB
9. Transfer Learning for Computer Vision/3. Large Datasets and Data Generators.mp4 38.3 MB
7. Natural Language Processing (NLP)/3. Text Preprocessing.mp4 37.9 MB
15. In-Depth Loss Functions/3. Categorical Cross Entropy.mp4 37.2 MB
3. Machine Learning and Neurons/10. Saving and Loading a Model.mp4 37.0 MB
16. In-Depth Gradient Descent/1. Gradient Descent.mp4 36.6 MB
5. Convolutional Neural Networks/8. CNN for CIFAR-10.mp4 36.5 MB
4. Feedforward Artificial Neural Networks/1. Artificial Neural Networks Section Introduction.mp4 34.1 MB
13. Advanced Tensorflow Usage/1. What is a Web Service (Tensorflow Serving pt 1).mp4 33.1 MB
9. Transfer Learning for Computer Vision/2. Some Pre-trained Models (VGG, ResNet, Inception, MobileNet).mp4 33.1 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/13. RNN for Image Classification (Theory).mp4 33.0 MB
3. Machine Learning and Neurons/5. Code Preparation (Regression Theory).mp4 32.9 MB
11. Deep Reinforcement Learning (Theory)/7. What does it mean to “learn”.mp4 31.8 MB
12. Stock Trading Project with Deep Reinforcement Learning/4. Program Design and Layout.mp4 31.2 MB
12. Stock Trading Project with Deep Reinforcement Learning/1. Reinforcement Learning Stock Trader Introduction.mp4 31.1 MB
1. Welcome/3. Where to get the code.mp4 30.9 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/18. Other Ways to Forecast.mp4 29.7 MB
5. Convolutional Neural Networks/3. What is Convolution (part 3).mp4 29.0 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/14. RNN for Image Classification (Code).mp4 28.8 MB
5. Convolutional Neural Networks/2. What is Convolution (part 2).mp4 26.4 MB
3. Machine Learning and Neurons/3. Beginner's Code Preamble.mp4 26.3 MB
16. In-Depth Gradient Descent/2. Stochastic Gradient Descent.mp4 26.3 MB
12. Stock Trading Project with Deep Reinforcement Learning/3. Replay Buffer.mp4 25.2 MB
15. In-Depth Loss Functions/2. Binary Cross Entropy.mp4 24.8 MB
5. Convolutional Neural Networks/10. Batch Normalization.mp4 24.6 MB
11. Deep Reinforcement Learning (Theory)/5. The Return.mp4 22.0 MB
9. Transfer Learning for Computer Vision/4. 2 Approaches to Transfer Learning.mp4 21.6 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/6. RNN Code Preparation.mp4 21.4 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/4. Proof that the Linear Model Works.mp4 19.2 MB
12. Stock Trading Project with Deep Reinforcement Learning/9. Reinforcement Learning Stock Trader Discussion.mp4 19.1 MB
21. Appendix FAQ/1. What is the Appendix.mp4 18.9 MB
3. Machine Learning and Neurons/11. Suggestion Box.mp4 16.9 MB
18. Setting up your Environment/3. Installing NVIDIA GPU-Accelerated Deep Learning Libraries on your Home Computer.srt 32.8 kB
20. Effective Learning Strategies for Machine Learning/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt 32.4 kB
5. Convolutional Neural Networks/5. CNN Architecture.srt 28.6 kB
11. Deep Reinforcement Learning (Theory)/2. Elements of a Reinforcement Learning Problem.srt 26.8 kB
6. Recurrent Neural Networks, Time Series, and Sequence Data/5. Recurrent Neural Networks.srt 26.2 kB
6. Recurrent Neural Networks, Time Series, and Sequence Data/1. Sequence Data.srt 24.6 kB
6. Recurrent Neural Networks, Time Series, and Sequence Data/12. Demo of the Long Distance Problem.srt 23.6 kB
20. Effective Learning Strategies for Machine Learning/4. What order should I take your courses in (part 2).srt 23.6 kB
4. Feedforward Artificial Neural Networks/4. Activation Functions.srt 23.2 kB
19. Extra Help With Python Coding for Beginners/1. How to Code Yourself (part 1).srt 22.7 kB
10. GANs (Generative Adversarial Networks)/1. GAN Theory.srt 21.2 kB
5. Convolutional Neural Networks/4. Convolution on Color Images.srt 21.0 kB
13. Advanced Tensorflow Usage/2. Tensorflow Serving pt 2.srt 20.9 kB
3. Machine Learning and Neurons/2. Code Preparation (Classification Theory).srt 20.7 kB
5. Convolutional Neural Networks/1. What is Convolution (part 1).srt 20.6 kB
18. Setting up your Environment/2. Windows-Focused Environment Setup 2018.srt 20.4 kB
5. Convolutional Neural Networks/6. CNN Code Preparation.srt 20.1 kB
3. Machine Learning and Neurons/1. What is Machine Learning.srt 18.9 kB
11. Deep Reinforcement Learning (Theory)/11. Q-Learning.srt 18.3 kB
8. Recommender Systems/1. Recommender Systems with Deep Learning Theory.srt 17.8 kB
1. Welcome/2. Outline.srt 17.5 kB
7. Natural Language Processing (NLP)/2. Code Preparation (NLP).srt 17.2 kB
11. Deep Reinforcement Learning (Theory)/12. Deep Q-Learning DQN (pt 1).srt 16.8 kB
4. Feedforward Artificial Neural Networks/7. Code Preparation (ANN).srt 16.7 kB
7. Natural Language Processing (NLP)/1. Embeddings.srt 16.6 kB
20. Effective Learning Strategies for Machine Learning/3. What order should I take your courses in (part 1).srt 16.5 kB
6. Recurrent Neural Networks, Time Series, and Sequence Data/15. Stock Return Predictions using LSTMs (pt 1).srt 16.1 kB
12. Stock Trading Project with Deep Reinforcement Learning/2. Data and Environment.srt 16.1 kB
4. Feedforward Artificial Neural Networks/6. How to Represent Images.srt 16.0 kB
16. In-Depth Gradient Descent/4. Variable and Adaptive Learning Rates.srt 15.5 kB
11. Deep Reinforcement Learning (Theory)/9. Solving the Bellman Equation with Reinforcement Learning (pt 2).srt 15.2 kB
10. GANs (Generative Adversarial Networks)/2. GAN Code.srt 15.2 kB
18. Setting up your Environment/1. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt 15.0 kB
20. Effective Learning Strategies for Machine Learning/1. How to Succeed in this Course (Long Version).srt 15.0 kB
6. Recurrent Neural Networks, Time Series, and Sequence Data/17. Stock Return Predictions using LSTMs (pt 3).srt 14.8 kB
6. Recurrent Neural Networks, Time Series, and Sequence Data/10. GRU and LSTM (pt 2).srt 14.6 kB
6. Recurrent Neural Networks, Time Series, and Sequence Data/3. Autoregressive Linear Model for Time Series Prediction.srt 14.6 kB
19. Extra Help With Python Coding for Beginners/3. Proof that using Jupyter Notebook is the same as not using it.srt 14.6 kB
2. Google Colab/1. Intro to Google Colab, how to use a GPU or TPU for free.srt 14.5 kB
3. Machine Learning and Neurons/8. How does a model learn.srt 14.3 kB
9. Transfer Learning for Computer Vision/5. Transfer Learning Code (pt 1).srt 14.1 kB
14. Low-Level Tensorflow/3. Variables and Gradient Tape.srt 13.9 kB
16. In-Depth Gradient Descent/5. Adam.srt 13.8 kB
6. Recurrent Neural Networks, Time Series, and Sequence Data/2. Forecasting.srt 13.7 kB
14. Low-Level Tensorflow/4. Build Your Own Custom Model.srt 13.6 kB
11. Deep Reinforcement Learning (Theory)/13. Deep Q-Learning DQN (pt 2).srt 13.5 kB
5. Convolutional Neural Networks/11. Improving CIFAR-10 Results.srt 13.5 kB
19. Extra Help With Python Coding for Beginners/2. How to Code Yourself (part 2).srt 13.3 kB
4. Feedforward Artificial Neural Networks/9. ANN for Regression.srt 13.1 kB
11. Deep Reinforcement Learning (Theory)/8. Solving the Bellman Equation with Reinforcement Learning (pt 1).srt 13.0 kB
11. Deep Reinforcement Learning (Theory)/4. Markov Decision Processes (MDPs).srt 13.0 kB
19. Extra Help With Python Coding for Beginners/4. Is Theano Dead.srt 12.9 kB
11. Deep Reinforcement Learning (Theory)/6. Value Functions and the Bellman Equation.srt 12.8 kB
3. Machine Learning and Neurons/7. The Neuron.srt 12.8 kB
4. Feedforward Artificial Neural Networks/2. Forward Propagation.srt 12.5 kB
14. Low-Level Tensorflow/1. Differences Between Tensorflow 1.x and Tensorflow 2.x.srt 12.5 kB
3. Machine Learning and Neurons/6. Regression Notebook.srt 12.4 kB
2. Google Colab/3. Uploading your own data to Google Colab.srt 12.3 kB
12. Stock Trading Project with Deep Reinforcement Learning/6. Code pt 2.srt 12.0 kB
8. Recommender Systems/2. Recommender Systems with Deep Learning Code.srt 12.0 kB
2. Google Colab/4. Where can I learn about Numpy, Scipy, Matplotlib, Pandas, and Scikit-Learn.srt 11.8 kB
4. Feedforward Artificial Neural Networks/3. The Geometrical Picture.srt 11.8 kB
11. Deep Reinforcement Learning (Theory)/3. States, Actions, Rewards, Policies.srt 11.6 kB
13. Advanced Tensorflow Usage/4. Why is Google the King of Distributed Computing.srt 11.5 kB
5. Convolutional Neural Networks/9. Data Augmentation.srt 11.5 kB
6. Recurrent Neural Networks, Time Series, and Sequence Data/7. RNN for Time Series Prediction.srt 11.5 kB
15. In-Depth Loss Functions/1. Mean Squared Error.srt 11.5 kB
13. Advanced Tensorflow Usage/3. Tensorflow Lite (TFLite).srt 11.3 kB
4. Feedforward Artificial Neural Networks/5. Multiclass Classification.srt 11.2 kB
9. Transfer Learning for Computer Vision/1. Transfer Learning Theory.srt 10.9 kB
9. Transfer Learning for Computer Vision/6. Transfer Learning Code (pt 2).srt 10.7 kB
7. Natural Language Processing (NLP)/5. CNNs for Text.srt 10.3 kB
4. Feedforward Artificial Neural Networks/8. ANN for Image Classification.srt 10.2 kB
6. Recurrent Neural Networks, Time Series, and Sequence Data/8. Paying Attention to Shapes.srt 10.1 kB
7. Natural Language Processing (NLP)/4. Text Classification with LSTMs.srt 10.0 kB
16. In-Depth Gradient Descent/1. Gradient Descent.srt 10.0 kB
14. Low-Level Tensorflow/2. Constants and Basic Computation.srt 9.9 kB
15. In-Depth Loss Functions/3. Categorical Cross Entropy.srt 9.9 kB
6. Recurrent Neural Networks, Time Series, and Sequence Data/11. A More Challenging Sequence.srt 9.8 kB
2. Google Colab/2. Tensorflow 2.0 in Google Colab.srt 9.7 kB
3. Machine Learning and Neurons/4. Classification Notebook.srt 9.6 kB
3. Machine Learning and Neurons/5. Code Preparation (Regression Theory).srt 9.3 kB
11. Deep Reinforcement Learning (Theory)/7. What does it mean to “learn”.srt 9.1 kB
9. Transfer Learning for Computer Vision/3. Large Datasets and Data Generators.srt 9.0 kB
12. Stock Trading Project with Deep Reinforcement Learning/4. Program Design and Layout.srt 8.8 kB
11. Deep Reinforcement Learning (Theory)/1. Deep Reinforcement Learning Section Introduction.srt 8.8 kB
13. Advanced Tensorflow Usage/5. Training with Distributed Strategies.srt 8.7 kB
12. Stock Trading Project with Deep Reinforcement Learning/8. Code pt 4.srt 8.4 kB
17. Extras/1. Links to TF2.0 Notebooks.html 8.3 kB
5. Convolutional Neural Networks/3. What is Convolution (part 3).srt 8.2 kB
3. Machine Learning and Neurons/9. Making Predictions.srt 8.2 kB
5. Convolutional Neural Networks/7. CNN for Fashion MNIST.srt 8.2 kB
4. Feedforward Artificial Neural Networks/1. Artificial Neural Networks Section Introduction.srt 8.1 kB
21. Appendix FAQ/2. BONUS Where to get discount coupons and FREE deep learning material.srt 8.1 kB
16. In-Depth Gradient Descent/3. Momentum.srt 8.0 kB
1. Welcome/3. Where to get the code.srt 8.0 kB
12. Stock Trading Project with Deep Reinforcement Learning/7. Code pt 3.srt 7.9 kB
13. Advanced Tensorflow Usage/1. What is a Web Service (Tensorflow Serving pt 1).srt 7.9 kB
11. Deep Reinforcement Learning (Theory)/14. How to Learn Reinforcement Learning.srt 7.8 kB
11. Deep Reinforcement Learning (Theory)/10. Epsilon-Greedy.srt 7.6 kB
9. Transfer Learning for Computer Vision/2. Some Pre-trained Models (VGG, ResNet, Inception, MobileNet).srt 7.5 kB
15. In-Depth Loss Functions/2. Binary Cross Entropy.srt 7.4 kB
5. Convolutional Neural Networks/2. What is Convolution (part 2).srt 7.4 kB
3. Machine Learning and Neurons/3. Beginner's Code Preamble.srt 7.4 kB
12. Stock Trading Project with Deep Reinforcement Learning/5. Code pt 1.srt 7.4 kB
6. Recurrent Neural Networks, Time Series, and Sequence Data/18. Other Ways to Forecast.srt 7.4 kB
6. Recurrent Neural Networks, Time Series, and Sequence Data/6. RNN Code Preparation.srt 7.3 kB
12. Stock Trading Project with Deep Reinforcement Learning/3. Replay Buffer.srt 7.1 kB
12. Stock Trading Project with Deep Reinforcement Learning/1. Reinforcement Learning Stock Trader Introduction.srt 7.0 kB
7. Natural Language Processing (NLP)/6. Text Classification with CNNs.srt 6.8 kB
5. Convolutional Neural Networks/10. Batch Normalization.srt 6.7 kB
6. Recurrent Neural Networks, Time Series, and Sequence Data/16. Stock Return Predictions using LSTMs (pt 2).srt 6.7 kB
11. Deep Reinforcement Learning (Theory)/5. The Return.srt 6.4 kB
7. Natural Language Processing (NLP)/3. Text Preprocessing.srt 6.3 kB
6. Recurrent Neural Networks, Time Series, and Sequence Data/13. RNN for Image Classification (Theory).srt 6.1 kB
9. Transfer Learning for Computer Vision/4. 2 Approaches to Transfer Learning.srt 6.1 kB
1. Welcome/1. Introduction.srt 5.8 kB
16. In-Depth Gradient Descent/2. Stochastic Gradient Descent.srt 5.5 kB
5. Convolutional Neural Networks/8. CNN for CIFAR-10.srt 5.5 kB
3. Machine Learning and Neurons/10. Saving and Loading a Model.srt 5.0 kB
3. Machine Learning and Neurons/11. Suggestion Box.srt 4.8 kB
6. Recurrent Neural Networks, Time Series, and Sequence Data/4. Proof that the Linear Model Works.srt 4.7 kB
12. Stock Trading Project with Deep Reinforcement Learning/9. Reinforcement Learning Stock Trader Discussion.srt 4.5 kB
6. Recurrent Neural Networks, Time Series, and Sequence Data/14. RNN for Image Classification (Code).srt 4.3 kB
21. Appendix FAQ/1. What is the Appendix.srt 3.8 kB
13. Advanced Tensorflow Usage/6. Using the TPU.html 1.8 kB
14. Low-Level Tensorflow/[DesireCourse.Net].url 51 Bytes
2. Google Colab/[DesireCourse.Net].url 51 Bytes
20. Effective Learning Strategies for Machine Learning/[DesireCourse.Net].url 51 Bytes
8. Recommender Systems/[DesireCourse.Net].url 51 Bytes
[DesireCourse.Net].url 51 Bytes
14. Low-Level Tensorflow/[CourseClub.Me].url 48 Bytes
2. Google Colab/[CourseClub.Me].url 48 Bytes
20. Effective Learning Strategies for Machine Learning/[CourseClub.Me].url 48 Bytes
8. Recommender Systems/[CourseClub.Me].url 48 Bytes
[CourseClub.Me].url 48 Bytes

==查看完整文档列表==

上一个：Keeping.Faith.S02.720p.TVShows5.5 GB
下一个：PRED-233-C 169.4 MB

24小时热门磁力链接

Andor [HDTV 720p][Cap.205] 8145次下载 Cap HDTV 720p
Маня и Груня.2024.WEB-DL 720p.Files-x 5109次下载 2024 WEB DL
Havoc.2025.1080p.NF.WEB-DL.DDP5.1.Atmos.H.264-EniaHD.mkv 5077次下载 WEB DL DDP5
The.Super.Cube.S01E09.1080p.iQ.WEB-DL.AAC2.0.H.264-VARYG.mkv 5040次下载 WEB DL Cube
Star.Wars.Andor.S02E05.I.Have.Friends.Everywhere.1080p.DS... 4944次下载 WEB DL Star
新桥恋人.电影港地址发布页 www.dygang.me 收藏不迷路 4365次下载 me www 发布页
Night at the Museum Battle of the Smithsonian 2009 2160p... 4161次下载 KiNGDOM WEB DL
www.UIndex.org - ... 4126次下载 www MeGusta HEVC
Palma.2.2024.WEB-DL.1080p.ExKinoRay.mkv 4000次下载 WEB DL 2.2024
Guns N' Roses - Greatest Hits Live Broadcast Collection... 3915次下载 Live Remastered Hits

本周热门磁力链接

Andor [HDTV 720p][Cap.205] 8145次下载 Cap HDTV 720p
(同人CG集) [白色絵の具 (無味ムスミ)] 友達の母が巨乳で金髪の淫乱美女でした.zip 6346次下载 zip 巨乳 CG
You.S05E02.720p.HEVC.x265-MeGusta[EZTVx.to].mkv 6221次下载 S05E02 HEVC 720p
up-mod-minecraft-play-with-friends-v1-21-80-28-... 6023次下载 982108028 mod play
the.last.of.us.s02e02.1080p.web.h264-successful... 5335次下载 web last h264
异世降临.6v电影地址发布页 www.6v123.net 收藏不迷路 5220次下载 www 发布页 6v123
Opasnaya.blizost.S01.2025.WEB-DL.1080p 5127次下载 WEB DL S01
Маня и Груня.2024.WEB-DL 720p.Files-x 5109次下载 2024 WEB DL
Andor.S02E02.Sagrona.Teema.1080p.HEVC.x265-MeGu... 5100次下载 HEVC Andor mkv
Havoc.2025.1080p.NF.WEB-DL.DDP5.1.Atmos.H.264-E... 5077次下载 WEB DL DDP5

种子标签

种子评价

优质的种子 (0) 假种子 (0) 有密码 (0) 低质量 (0) 有病毒 (0) 无法下载 (0)
欢迎对种子质量进行评价。

人气女优

北川ゆい Akira COCOLO Saiko あいだももあさのくるみあまいれもんいしかわ愛里いとうしいなうさみ恭香うちだまひろかぐやひめかとりこのみかないかほくすのき琴美クミコグレースくらもとまい（葉月ありさ）さとみ中村あみしいな純菜しのざきさとみ（三沢亜也）牧本千幸（つかもと友希）眞木ありさデヴィテラパトリックドミニカともさかまいともさか愛なごみもえひなこ

分享BT种子/磁力链接

亲，你知道吗？下载的人越多速度越快，赶快把本页面分享给好友一起下载吧^_^

磁力管家