tensorflow - 磁力狗 - 最好用的磁力种子搜索引擎

【压缩文件】 Udemy.Tensorflow.Guía.completa.para.Nuevo.Tensorflow

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Udemy.Tensorflow.Guía.completa.para.Nuevo.Tensorflow.rar 5.5 GB

猜你喜欢： Tensorflow completa Gu para Udemy Nuevo

【影视】 [GigaCourse.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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【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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【影视】 [DesireCourse.Net] 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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【影视】 [DesireCourse.Net] 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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【影视】 [FreeCourseSite.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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【影视】 [FreeCourseSite.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

猜你喜欢： Complete FreeCourseSite Keras Udemy API using TensorFlow 2.0 com Guide

【影视】 [Udemy] A Complete Guide on TensorFlow 2.0 using Keras API (2021) [En]

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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】 [DesireCourse.Net] 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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【其他】 [DesireCourse.Net] 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.!qB 203.6 MB
17. Annex 3 - Recurrent Neural Networks Theory/5. LSTM Practical Intuition.mp4.!qB 196.5 MB
1. Introduction/1. Welcome to the TensorFlow 2.0 course! Discover its structure and the TF toolkit..mp4.!qB 153.4 MB
16. Annex 2 - Convolutional Neural Networks Theory/5. Step 2 - Max Pooling.mp4.!qB 143.9 MB
17. Annex 3 - Recurrent Neural Networks Theory/4. LSTMs.mp4.!qB 143.1 MB
7. Deep Reinforcement Learning Theory/9. Action Selection Policies.mp4.!qB 141.3 MB
17. Annex 3 - Recurrent Neural Networks Theory/2. What are Recurrent Neural Networks.mp4.!qB 126.8 MB
16. Annex 2 - Convolutional Neural Networks Theory/9. Softmax & Cross-Entropy.mp4.!qB 123.6 MB
2. TensorFlow 2.0 Basics/1. From TensorFlow 1.x to TensorFlow 2.0.mp4.!qB 120.4 MB
7. Deep Reinforcement Learning Theory/8. Experience Replay.mp4.!qB 117.9 MB
15. Annex 1 - Artificial Neural Networks Theory/5. How do Neural Networks Learn.mp4.!qB 117.6 MB
17. Annex 3 - Recurrent Neural Networks Theory/3. Vanishing Gradient.mp4.!qB 116.4 MB
16. Annex 2 - Convolutional Neural Networks Theory/2. What are Convolutional Neural Networks.mp4.!qB 113.1 MB
7. Deep Reinforcement Learning Theory/6. Deep Q-Learning Intuition - Step 1.mp4.!qB 104.3 MB
15. Annex 1 - Artificial Neural Networks Theory/2. The Neuron.mp4.!qB 103.5 MB
16. Annex 2 - Convolutional Neural Networks Theory/3. Step 1 - Convolution.mp4.!qB 102.6 MB
7. Deep Reinforcement Learning Theory/5. Temporal Difference.mp4.!qB 101.8 MB
7. Deep Reinforcement Learning Theory/2. The Bellman Equation.mp4.!qB 99.7 MB
7. Deep Reinforcement Learning Theory/3. Markov Decision Process (MDP).mp4.!qB 98.9 MB
4. Convolutional Neural Networks/2. Building the Convolutional Neural Network.mp4.!qB 92.5 MB

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【压缩文件】 Tensorflow and Keras For Neural Networks and Deep Learning

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Tensorflow and Keras For Neural Networks and Deep Learning.zip 5.3 GB
Download more courses.url 123 Bytes
Downloaded from TutsGalaxy.com.txt 73 Bytes
TutsGalaxy.com.txt 52 Bytes

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【压缩文件】 Deep learning for object detection using Tensorflow 2

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Deep learning for object detection using Tensorflow 2.zip 5.0 GB
[TGx]Downloaded from torrentgalaxy.to .txt 585 Bytes
TutsNode.com.txt 63 Bytes

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【压缩文件】 [FreeCourseSite.com] Udemy - TensorFlow 2.0 Practical Advanced

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[FreeCourseSite.com] Udemy - TensorFlow 2.0 Practical Advanced.part1.rar 2.1 GB
[FreeCourseSite.com] Udemy - TensorFlow 2.0 Practical Advanced.part2.rar 2.1 GB
[FreeCourseSite.com] Udemy - TensorFlow 2.0 Practical Advanced.part3.rar 729.6 MB

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【影视】 Tensorflow 2.0 Um Guia Completo sobre o novo TensorFlow

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16. Anexo III - Redes Neurais Recorrentes - teoria/4. Intuição prática.mp4 166.4 MB
16. Anexo III - Redes Neurais Recorrentes - teoria/3. Long short term memory - LSTM.mp4 104.1 MB
16. Anexo III - Redes Neurais Recorrentes - teoria/1. O que são Redes Neurais Recorrentes.mp4 103.1 MB
17. Anexo IV - Aprendizagem por Reforço Profunda - teoria/2. A Equação de Bellman.mp4 95.1 MB
14. Anexo I - Redes Neurais Artificiais - teoria/9. Funções de ativação II.mp4 81.5 MB
15. Anexo II - Redes Neurais Convolucionais - teoria/2. Introdução a redes neurais convolucionais II.mp4 80.5 MB
15. Anexo II - Redes Neurais Convolucionais - teoria/1. Introdução a redes neurais convolucionais I.mp4 75.9 MB
7. Aprendizagem por Reforço Profunda para Negociação no Mercado de Ações/12. Treinamento II.mp4 75.6 MB
17. Anexo IV - Aprendizagem por Reforço Profunda - teoria/11. Replay de Experiência.mp4 75.2 MB
17. Anexo IV - Aprendizagem por Reforço Profunda - teoria/12. Políticas de Seleções de Ações.mp4 74.6 MB
2. Básico do TensorFlow/1. Do TensorFlow 1.x para o TensorFlow 2.0 - Constantes, variáveis e tensores.mp4 72.9 MB
1. Introdução/1. Bem-vindo(a) ao curso!.mp4 72.3 MB
16. Anexo III - Redes Neurais Recorrentes - teoria/2. Problema do gradiente desaparecendo (vanish gradient problem).mp4 71.0 MB
10. API com Flask e TensorFlow 2.0/1. Configuração do Projeto.mp4 70.3 MB
17. Anexo IV - Aprendizagem por Reforço Profunda - teoria/4. Markov Decision Process - MDP.mp4 70.3 MB
5. Redes Neurais Recorrentes/1. Configuração do Projeto e Pré-processamento.mp4 66.1 MB
15. Anexo II - Redes Neurais Convolucionais - teoria/6. Etapa 3 - flattening.mp4 65.8 MB
15. Anexo II - Redes Neurais Convolucionais - teoria/7. Etapa 4 - rede neural densa.mp4 65.3 MB
9. Pré-processamento de Dados com TFT (TensorFlow Transform)/5. Pipeline de Pré-processamento.mp4 63.7 MB
7. Aprendizagem por Reforço Profunda para Negociação no Mercado de Ações/6. IA Trader 5.mp4 63.4 MB

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【影视】 Tensorflow 2.0 Um Guia Completo sobre o novo TensorFlow

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16. Anexo III - Redes Neurais Recorrentes - teoria/4. Intuição prática.mp4 166.4 MB
16. Anexo III - Redes Neurais Recorrentes - teoria/3. Long short term memory - LSTM.mp4 104.1 MB
16. Anexo III - Redes Neurais Recorrentes - teoria/1. O que são Redes Neurais Recorrentes.mp4 103.1 MB
17. Anexo IV - Aprendizagem por Reforço Profunda - teoria/2. A Equação de Bellman.mp4 95.1 MB
14. Anexo I - Redes Neurais Artificiais - teoria/9. Funções de ativação II.mp4 81.5 MB
15. Anexo II - Redes Neurais Convolucionais - teoria/2. Introdução a redes neurais convolucionais II.mp4 80.5 MB
15. Anexo II - Redes Neurais Convolucionais - teoria/1. Introdução a redes neurais convolucionais I.mp4 75.9 MB
7. Aprendizagem por Reforço Profunda para Negociação no Mercado de Ações/12. Treinamento II.mp4 75.6 MB
17. Anexo IV - Aprendizagem por Reforço Profunda - teoria/11. Replay de Experiência.mp4 75.2 MB
17. Anexo IV - Aprendizagem por Reforço Profunda - teoria/12. Políticas de Seleções de Ações.mp4 74.6 MB
2. Básico do TensorFlow/1. Do TensorFlow 1.x para o TensorFlow 2.0 - Constantes, variáveis e tensores.mp4 72.9 MB
1. Introdução/1. Bem-vindo(a) ao curso!.mp4 72.3 MB
16. Anexo III - Redes Neurais Recorrentes - teoria/2. Problema do gradiente desaparecendo (vanish gradient problem).mp4 71.0 MB
10. API com Flask e TensorFlow 2.0/1. Configuração do Projeto.mp4 70.3 MB
17. Anexo IV - Aprendizagem por Reforço Profunda - teoria/4. Markov Decision Process - MDP.mp4 70.3 MB
5. Redes Neurais Recorrentes/1. Configuração do Projeto e Pré-processamento.mp4 66.1 MB
15. Anexo II - Redes Neurais Convolucionais - teoria/6. Etapa 3 - flattening.mp4 65.8 MB
15. Anexo II - Redes Neurais Convolucionais - teoria/7. Etapa 4 - rede neural densa.mp4 65.3 MB
9. Pré-processamento de Dados com TFT (TensorFlow Transform)/5. Pipeline de Pré-processamento.mp4 63.7 MB
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16. Anexo III - Redes Neurais Recorrentes - teoria/4. Intuição prática.mp4 166.4 MB
16. Anexo III - Redes Neurais Recorrentes - teoria/3. Long short term memory - LSTM.mp4 104.1 MB
16. Anexo III - Redes Neurais Recorrentes - teoria/1. O que são Redes Neurais Recorrentes.mp4 103.1 MB
17. Anexo IV - Aprendizagem por Reforço Profunda - teoria/2. A Equação de Bellman.mp4 95.1 MB
14. Anexo I - Redes Neurais Artificiais - teoria/9. Funções de ativação II.mp4 81.5 MB
15. Anexo II - Redes Neurais Convolucionais - teoria/2. Introdução a redes neurais convolucionais II.mp4 80.5 MB
15. Anexo II - Redes Neurais Convolucionais - teoria/1. Introdução a redes neurais convolucionais I.mp4 75.9 MB
7. Aprendizagem por Reforço Profunda para Negociação no Mercado de Ações/12. Treinamento II.mp4 75.6 MB
17. Anexo IV - Aprendizagem por Reforço Profunda - teoria/11. Replay de Experiência.mp4 75.2 MB
17. Anexo IV - Aprendizagem por Reforço Profunda - teoria/12. Políticas de Seleções de Ações.mp4 74.6 MB
2. Básico do TensorFlow/1. Do TensorFlow 1.x para o TensorFlow 2.0 - Constantes, variáveis e tensores.mp4 72.9 MB
1. Introdução/1. Bem-vindo(a) ao curso!.mp4 72.3 MB
16. Anexo III - Redes Neurais Recorrentes - teoria/2. Problema do gradiente desaparecendo (vanish gradient problem).mp4 71.0 MB
10. API com Flask e TensorFlow 2.0/1. Configuração do Projeto.mp4 70.3 MB
17. Anexo IV - Aprendizagem por Reforço Profunda - teoria/4. Markov Decision Process - MDP.mp4 70.3 MB
5. Redes Neurais Recorrentes/1. Configuração do Projeto e Pré-processamento.mp4 66.1 MB
15. Anexo II - Redes Neurais Convolucionais - teoria/6. Etapa 3 - flattening.mp4 65.8 MB
15. Anexo II - Redes Neurais Convolucionais - teoria/7. Etapa 4 - rede neural densa.mp4 65.3 MB
9. Pré-processamento de Dados com TFT (TensorFlow Transform)/5. Pipeline de Pré-processamento.mp4 63.7 MB
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~Get Your Files Here !/1. Chapter 1/18. 14. Classes And Objects.mp4 234.1 MB
~Get Your Files Here !/1. Chapter 1/15. 11. Loops.mp4 175.2 MB
~Get Your Files Here !/1. Chapter 1/7. 03. Operators.mp4 169.3 MB
~Get Your Files Here !/1. Chapter 1/19. 15. Inheritance Examples.mp4 137.0 MB
~Get Your Files Here !/1. Chapter 1/14. 10. If Statement Examples.mp4 123.8 MB
~Get Your Files Here !/4. 07 Data analysis and transformation on blood cell data/3. 02 Clean Data With Missing Values.mp4 123.2 MB
~Get Your Files Here !/1. Chapter 1/9. 05. List Examples.mp4 115.1 MB
~Get Your Files Here !/1. Chapter 1/5. 01. Variables.mp4 111.6 MB
~Get Your Files Here !/10. 13 Prepare heart disease data for machine learning/2. 02 Clean And Preprocess Heart Disease Data For Machine Learning.mp4 109.1 MB
~Get Your Files Here !/3. 06 Build Regression Machine Learning Models to Detect Diabetes/3. 04 Select Top Features Via Variance Threshold.mp4 108.0 MB
~Get Your Files Here !/1. Chapter 1/11. 07. Dictionaries Examples.mp4 91.5 MB
~Get Your Files Here !/1. Chapter 1/16. 12. Functions.mp4 90.6 MB
~Get Your Files Here !/1. Chapter 1/27. 02 What Is Regression.mp4 87.8 MB
~Get Your Files Here !/10. 13 Prepare heart disease data for machine learning/1. 01 Load Data Via Data File.mp4 87.1 MB
~Get Your Files Here !/2. 05 Build a K Nearest neighbors regression model to predict diabetes/2. 01 Load And Analyze Data.mp4 84.3 MB
~Get Your Files Here !/1. Chapter 1/20. 16. Static Members Examples.mp4 82.4 MB
~Get Your Files Here !/1. Chapter 1/17. 13. Parameters And Return Values Examples.mp4 82.3 MB
~Get Your Files Here !/2. 05 Build a K Nearest neighbors regression model to predict diabetes/4. 02 Build A K Nearest Neighbors Regression Model To Predict Diabetes.mp4 81.3 MB
~Get Your Files Here !/4. 07 Data analysis and transformation on blood cell data/2. 01 Load And Analyze Blood Cell Data.mp4 78.6 MB
~Get Your Files Here !/13. 16 Build a neural network to find malaria in cells/6. 05 Train And Evaluate Model Accuracy.mp4 76.6 MB

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A Practical Guide to Deep Learning with TensorFlow 2.0 and K (28).mp4 196.5 MB
A Practical Guide to Deep Learning with TensorFlow 2.0 and K (27).mp4 188.6 MB
A Practical Guide to Deep Learning with TensorFlow 2.0 and K (2).mp4 188.1 MB
A Practical Guide to Deep Learning with TensorFlow 2.0 and K (20).mp4 185.1 MB
A Practical Guide to Deep Learning with TensorFlow 2.0 and K (25).mp4 179.8 MB
A Practical Guide to Deep Learning with TensorFlow 2.0 and K (3).mp4 179.5 MB
A Practical Guide to Deep Learning with TensorFlow 2.0 and K (22).mp4 177.9 MB
A Practical Guide to Deep Learning with TensorFlow 2.0 and K (26).mp4 177.8 MB
A Practical Guide to Deep Learning with TensorFlow 2.0 and K (21).mp4 176.5 MB
A Practical Guide to Deep Learning with TensorFlow 2.0 and K (7).mp4 176.3 MB
A Practical Guide to Deep Learning with TensorFlow 2.0 and K (16).mp4 173.7 MB
A Practical Guide to Deep Learning with TensorFlow 2.0 and K (18).mp4 173.7 MB
A Practical Guide to Deep Learning with TensorFlow 2.0 and K (5).mp4 171.0 MB
A Practical Guide to Deep Learning with TensorFlow 2.0 and K (1).mp4 170.6 MB
A Practical Guide to Deep Learning with TensorFlow 2.0 and K (10).mp4 167.2 MB
A Practical Guide to Deep Learning with TensorFlow 2.0 and K (11).mp4 165.6 MB
A Practical Guide to Deep Learning with TensorFlow 2.0 and K (9).mp4 164.8 MB
A Practical Guide to Deep Learning with TensorFlow 2.0 and K (6).mp4 161.7 MB
A Practical Guide to Deep Learning with TensorFlow 2.0 and K (15).mp4 147.8 MB
A Practical Guide to Deep Learning with TensorFlow 2.0 and K (17).mp4 140.9 MB

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15. R - Saving and Restoring Models/1. Saving - Restoring Models and Using Callbacks.mp4 226.6 MB
12. Python - Regression problems and Functional API/1. Building Neural Network for Regression Problem.mp4 163.4 MB
14. Python - Saving and Restoring Models/1. Saving - Restoring Models and Using Callbacks.mp4 159.0 MB
13. R - Regression Problem and Functional API/1. Building Regression Model with Functional AP.mp4 137.5 MB
11. R - Building and training the Model/1. Building,Compiling and Training.mp4 137.1 MB
5. Neural Networks - Stacking cells to create network/3. Back Propagation.mp4 128.1 MB
9. Dataset for classification problem/3. R - Dataset, Normalization and Test-Train set.mp4 117.2 MB
18. Add on Data Preprocessing/16. Bi-variate Analysis and Variable Transformation.mp4 105.4 MB
11. R - Building and training the Model/2. Evaluating and Predicting.mp4 104.1 MB
18. Add on Data Preprocessing/8. EDD in R.mp4 101.7 MB
3. Setting up R Studio and R Crash Course/7. Creating Barplots in R.mp4 101.5 MB
12. Python - Regression problems and Functional API/2. Using Functional API for complex architectures.mp4 96.6 MB
4. Single Cells - Perceptron and Sigmoid Neuron/3. Python - Creating Perceptron model.mp4 90.8 MB
3. Setting up R Studio and R Crash Course/3. Packages in R.mp4 87.0 MB
10. Python - Building and training the Model/3. Compiling and Training the Neural Network model.mp4 85.6 MB
13. R - Regression Problem and Functional API/2. Complex Architectures using Functional API.mp4 83.4 MB
10. Python - Building and training the Model/2. Building the Neural Network using Keras.mp4 83.0 MB
19. Test Train Split/4. Test train split in R.mp4 79.3 MB
18. Add on Data Preprocessing/10. Outlier Treatment in Python.mp4 73.7 MB
10. Python - Building and training the Model/4. Evaluating performance and Predicting using Keras.mp4 73.3 MB

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