- 【影视】 Udemy - TensorFlow 2.0 Practical Advanced [Dr. Ryan Ahmed, Ligency Team, Mitchell Bouchard] [En.Sub.]
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收录时间:2023-03-11
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01 - INTRODUCTION AND COURSE OUTLINE/007 Whats New in TensorFlow 2.0.mp4 229.6 MB
05 - DEEP DREAM/008 Deep Dream Coding P5.mp4 221.2 MB
05 - DEEP DREAM/001 What is Deep Dream.mp4 203.4 MB
05 - DEEP DREAM/002 How does DeepDream Algo work.mp4 162.6 MB
04 - AUTOENCODERS/20087012-traffic-signs-data.iso 159.7 MB
02 - REVIEW OF ARTIFICIAL NEURAL NETWORKS AND CONVOLUTIONAL NEURAL NETWORKS/001 ANN and CNN - Part 1.mp4 149.3 MB
04 - AUTOENCODERS/013 Autoencoders Project 2 - Coding P2.mp4 147.5 MB
04 - AUTOENCODERS/001 Autoencoders intuition.mp4 124.4 MB
03 - TRANSFER LEARNING (TF HUB)/006 Transfer Learning Project 1 - Coding P2.mp4 114.9 MB
02 - REVIEW OF ARTIFICIAL NEURAL NETWORKS AND CONVOLUTIONAL NEURAL NETWORKS/010 Project 1 - Solution Part 2.mp4 106.3 MB
06 - GANs/010 GANS Project 1 P5.mp4 102.1 MB
08 - TENSORFLOW SERVING AND TENSORBOARD/003 TF Serving Coding Part 3.mp4 102.1 MB
05 - DEEP DREAM/007 Deep Dream Coding P4.mp4 101.9 MB
02 - REVIEW OF ARTIFICIAL NEURAL NETWORKS AND CONVOLUTIONAL NEURAL NETWORKS/007 ANN and CNN - Part 7.mp4 100.3 MB
07 - RECURRENT NEURAL NETWORKS (RNNs) AND LSTMs/006 Vanishing Gradient Problem.mp4 100.3 MB
07 - RECURRENT NEURAL NETWORKS (RNNs) AND LSTMs/007 Long Short Term Memory LSTM.mp4 96.7 MB
01 - INTRODUCTION AND COURSE OUTLINE/004 ML, AI and DL.mp4 96.2 MB
06 - GANs/001 GANS intuition.mp4 95.4 MB
03 - TRANSFER LEARNING (TF HUB)/005 Transfer Learning Project 1 - Coding P1.mp4 93.8 MB
03 - TRANSFER LEARNING (TF HUB)/007 Transfer Learning Project 1 - Coding P3.mp4 92.6 MB
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- 【影视】 Udemy - Tensorflow 2.0 Deep Learning and Artificial Intelligence
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收录时间:2020-12-04
文档个数:246
文档大小:7.5 GB
最近下载:2023-11-14
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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
19. Appendix FAQ/9. What order should I take your courses in (part 2).mp4 128.6 MB
19. Appendix FAQ/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 96.6 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
19. Appendix FAQ/8. 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 90.5 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
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- 【影视】 [FreeAllCourse.Com] Udemy - A Complete Guide on TensorFlow 2.0 using Keras API
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16. Annex 2 - Convolutional Neural Networks Theory/7. Step 4 - Full Connection.mp4 203.6 MB
17. Annex 3 - Recurrent Neural Networks Theory/5. LSTM Practical Intuition.mp4 196.5 MB
1. Introduction/1. Welcome to the TensorFlow 2.0 course! Discover its structure and the TF toolkit..mp4 153.4 MB
16. Annex 2 - Convolutional Neural Networks Theory/5. Step 2 - Max Pooling.mp4 147.0 MB
7. Deep Reinforcement Learning Theory/9. Action Selection Policies.mp4 143.5 MB
17. Annex 3 - Recurrent Neural Networks Theory/4. LSTMs.mp4 143.1 MB
17. Annex 3 - Recurrent Neural Networks Theory/2. What are Recurrent Neural Networks.mp4 126.8 MB
16. Annex 2 - Convolutional Neural Networks Theory/9. Softmax & Cross-Entropy.mp4 123.6 MB
2. TensorFlow 2.0 Basics/1. From TensorFlow 1.x to TensorFlow 2.0.mp4 120.4 MB
7. Deep Reinforcement Learning Theory/8. Experience Replay.mp4 120.3 MB
15. Annex 1 - Artificial Neural Networks Theory/5. How do Neural Networks Learn.mp4 117.6 MB
17. Annex 3 - Recurrent Neural Networks Theory/3. Vanishing Gradient.mp4 116.4 MB
16. Annex 2 - Convolutional Neural Networks Theory/2. What are Convolutional Neural Networks.mp4 113.1 MB
7. Deep Reinforcement Learning Theory/6. Deep Q-Learning Intuition - Step 1.mp4 104.8 MB
15. Annex 1 - Artificial Neural Networks Theory/2. The Neuron.mp4 103.5 MB
16. Annex 2 - Convolutional Neural Networks Theory/3. Step 1 - Convolution.mp4 102.6 MB
7. Deep Reinforcement Learning Theory/5. Temporal Difference.mp4 101.8 MB
7. Deep Reinforcement Learning Theory/2. The Bellman Equation.mp4 99.7 MB
7. Deep Reinforcement Learning Theory/3. Markov Decision Process (MDP).mp4 98.9 MB
4. Convolutional Neural Networks/2. Building the Convolutional Neural Network.mp4 92.5 MB
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17. Annex 3 - Recurrent Neural Networks Theory/5. LSTM Practical Intuition.mp4 196.5 MB
16. Annex 2 - Convolutional Neural Networks Theory/5. Step 2 - Max Pooling.srt 147.0 MB
16. Annex 2 - Convolutional Neural Networks Theory/5. Step 2 - Max Pooling.mp4 147.0 MB
17. Annex 3 - Recurrent Neural Networks Theory/4. LSTMs.mp4 143.1 MB
2. TensorFlow 2.0 Basics/1. From TensorFlow 1.x to TensorFlow 2.0.mp4 120.4 MB
17. Annex 3 - Recurrent Neural Networks Theory/3. Vanishing Gradient.mp4 116.4 MB
15. Annex 1 - Artificial Neural Networks Theory/2. The Neuron.mp4 103.5 MB
16. Annex 2 - Convolutional Neural Networks Theory/3. Step 1 - Convolution.mp4 102.6 MB
2. TensorFlow 2.0 Basics/2. Constants, Variables, Tensors.mp4 74.8 MB
3. Artificial Neural Networks/2. Data Preprocessing.mp4 64.8 MB
15. Annex 1 - Artificial Neural Networks Theory/6. Gradient Descent.mp4 63.5 MB
3. Artificial Neural Networks/3. Building the Artificial Neural Network.mp4 63.4 MB
3. Artificial Neural Networks/1. Project Setup.mp4 62.1 MB
11. Fashion API with Flask and TensorFlow 2.0/5. Creating classify function.mp4 55.7 MB
2. TensorFlow 2.0 Basics/3. Operations with Tensors.mp4 51.6 MB
3. Artificial Neural Networks/4. Training the Artificial Neural Network.mp4 50.9 MB
4. Convolutional Neural Networks/1. Project Setup & Data Preprocessing.mp4 49.7 MB
15. Annex 1 - Artificial Neural Networks Theory/3. The Activation Function.mp4 47.5 MB
15. Annex 1 - Artificial Neural Networks Theory/8. Backpropagation.mp4 45.2 MB
2. TensorFlow 2.0 Basics/4. Strings.mp4 42.2 MB
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- 【影视】 [DownTuts.Com] Udemy - TensorFlow Developer Certificate in 2021 Zero to Mastery
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[DownTuts.Com] Udemy - TensorFlow Developer Certificate in 2021 Zero to Mastery 36.6 GB
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- 【影视】 [GigaCourse.com] Udemy - A Complete Guide on TensorFlow 2.0 using Keras API
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收录时间:2020-07-10
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16. Annex 2 - Convolutional Neural Networks Theory/7. Step 4 - Full Connection.mp4 203.6 MB
17. Annex 3 - Recurrent Neural Networks Theory/5. LSTM Practical Intuition.mp4 196.5 MB
1. Introduction/1. Welcome to the TensorFlow 2.0 course! Discover its structure and the TF toolkit..mp4 153.4 MB
16. Annex 2 - Convolutional Neural Networks Theory/5. Step 2 - Max Pooling.mp4 147.0 MB
7. Deep Reinforcement Learning Theory/9. Action Selection Policies.mp4 143.5 MB
17. Annex 3 - Recurrent Neural Networks Theory/4. LSTMs.mp4 143.1 MB
17. Annex 3 - Recurrent Neural Networks Theory/2. What are Recurrent Neural Networks.mp4 126.8 MB
16. Annex 2 - Convolutional Neural Networks Theory/9. Softmax & Cross-Entropy.mp4 123.6 MB
2. TensorFlow 2.0 Basics/1. From TensorFlow 1.x to TensorFlow 2.0.mp4 120.4 MB
7. Deep Reinforcement Learning Theory/8. Experience Replay.mp4 120.3 MB
15. Annex 1 - Artificial Neural Networks Theory/5. How do Neural Networks Learn.mp4 117.6 MB
17. Annex 3 - Recurrent Neural Networks Theory/3. Vanishing Gradient.mp4 116.4 MB
16. Annex 2 - Convolutional Neural Networks Theory/2. What are Convolutional Neural Networks.mp4 113.1 MB
7. Deep Reinforcement Learning Theory/6. Deep Q-Learning Intuition - Step 1.mp4 104.8 MB
15. Annex 1 - Artificial Neural Networks Theory/2. The Neuron.mp4 103.5 MB
16. Annex 2 - Convolutional Neural Networks Theory/3. Step 1 - Convolution.mp4 102.6 MB
7. Deep Reinforcement Learning Theory/5. Temporal Difference.mp4 101.8 MB
7. Deep Reinforcement Learning Theory/2. The Bellman Equation.mp4 99.7 MB
7. Deep Reinforcement Learning Theory/3. Markov Decision Process (MDP).mp4 98.9 MB
4. Convolutional Neural Networks/2. Building the Convolutional Neural Network.mp4 92.5 MB
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- 【影视】 Deep learning with TensorFlow [Video]
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19-skflow.mp4 36.1 MB
18-Introducing Recurrent Neural Networks.mp4 34.9 MB
04-Logistic Regression Model Building.mp4 27.1 MB
21-Research Evaluation.mp4 27.0 MB
12-Convolutional Layer Application.mp4 26.9 MB
15-Deep CNN.mp4 25.2 MB
02-Installing TensorFlow.mp4 21.5 MB
03-Simple Computations.mp4 21.4 MB
09-Multiple Hidden Layer Model.mp4 20.8 MB
06-Basic Neural Nets.mp4 20.3 MB
07-Single Hidden Layer Model.mp4 19.8 MB
05-Logistic Regression Training.mp4 19.2 MB
17-Wrapping Up Deep CNN.mp4 19.2 MB
10-Multiple Hidden Layer Results.mp4 18.2 MB
08-Single Hidden Layer Explained.mp4 17.9 MB
14-Pooling Layer Application.mp4 16.8 MB
16-Deeper CNN.mp4 16.3 MB
20-RNNs in skflow.mp4 15.7 MB
11-Convolutional Layer Motivation.mp4 13.4 MB
01-The Course Overview.mp4 11.6 MB
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16. Annex 2 - Convolutional Neural Networks Theory/7. Step 4 - Full Connection.mp4 203.6 MB
17. Annex 3 - Recurrent Neural Networks Theory/5. LSTM Practical Intuition.mp4 196.5 MB
1. Introduction/1. Welcome to the TensorFlow 2.0 course! Discover its structure and the TF toolkit..mp4 153.4 MB
16. Annex 2 - Convolutional Neural Networks Theory/5. Step 2 - Max Pooling.srt 147.0 MB
16. Annex 2 - Convolutional Neural Networks Theory/5. Step 2 - Max Pooling.mp4 147.0 MB
7. Deep Reinforcement Learning Theory/9. Action Selection Policies.mp4 143.5 MB
17. Annex 3 - Recurrent Neural Networks Theory/4. LSTMs.mp4 143.1 MB
17. Annex 3 - Recurrent Neural Networks Theory/2. What are Recurrent Neural Networks.mp4 126.8 MB
16. Annex 2 - Convolutional Neural Networks Theory/9. Softmax & Cross-Entropy.mp4 123.6 MB
2. TensorFlow 2.0 Basics/1. From TensorFlow 1.x to TensorFlow 2.0.mp4 120.4 MB
7. Deep Reinforcement Learning Theory/8. Experience Replay.mp4 120.3 MB
15. Annex 1 - Artificial Neural Networks Theory/5. How do Neural Networks Learn.mp4 117.6 MB
17. Annex 3 - Recurrent Neural Networks Theory/3. Vanishing Gradient.mp4 116.4 MB
16. Annex 2 - Convolutional Neural Networks Theory/2. What are Convolutional Neural Networks.mp4 113.1 MB
7. Deep Reinforcement Learning Theory/6. Deep Q-Learning Intuition - Step 1.mp4 104.8 MB
15. Annex 1 - Artificial Neural Networks Theory/2. The Neuron.mp4 103.5 MB
16. Annex 2 - Convolutional Neural Networks Theory/3. Step 1 - Convolution.mp4 102.6 MB
7. Deep Reinforcement Learning Theory/5. Temporal Difference.mp4 101.8 MB
7. Deep Reinforcement Learning Theory/2. The Bellman Equation.mp4 99.7 MB
7. Deep Reinforcement Learning Theory/3. Markov Decision Process (MDP).mp4 98.9 MB
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