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

Torrent Hash:
FF37CE1043E06BA5A6B030AF42C408CF579F652E
Number of Files:
246
Content Size:
6.73GB
Convert On:
2020-09-05
Keywords:
DesireCourseNetUdemyTensorflowDeepLearningandArtificialIntelligence
Magnet Link:
Download
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File Name
Size
1. Welcome/1. Introduction.mp4
39.15MB
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1. Welcome/1. Introduction.vtt
5.04KB
1. Welcome/2. Outline.mp4
30.81MB
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1. Welcome/2. Outline.vtt
6.37KB
1. Welcome/3. Where to get the code.mp4
30.48MB
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1. Welcome/3. Where to get the code.vtt
6.64KB
10. GANs (Generative Adversarial Networks)/1. GAN Theory.mp4
86.53MB
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10. GANs (Generative Adversarial Networks)/1. GAN Theory.vtt
18.09KB
10. GANs (Generative Adversarial Networks)/2. GAN Code.mp4
78.19MB
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10. GANs (Generative Adversarial Networks)/2. GAN Code.vtt
13.02KB
11. Deep Reinforcement Learning (Theory)/1. Deep Reinforcement Learning Section Introduction.mp4
37.77MB
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11. Deep Reinforcement Learning (Theory)/1. Deep Reinforcement Learning Section Introduction.vtt
7.49KB
11. Deep Reinforcement Learning (Theory)/10. Epsilon-Greedy.mp4
37.58MB
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11. Deep Reinforcement Learning (Theory)/10. Epsilon-Greedy.vtt
6.54KB
11. Deep Reinforcement Learning (Theory)/11. Q-Learning.mp4
61.28MB
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11. Deep Reinforcement Learning (Theory)/11. Q-Learning.vtt
15.63KB
11. Deep Reinforcement Learning (Theory)/12. Deep Q-Learning DQN (pt 1).mp4
55.7MB
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11. Deep Reinforcement Learning (Theory)/12. Deep Q-Learning DQN (pt 1).vtt
14.4KB
11. Deep Reinforcement Learning (Theory)/13. Deep Q-Learning DQN (pt 2).mp4
49.2MB
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11. Deep Reinforcement Learning (Theory)/13. Deep Q-Learning DQN (pt 2).vtt
11.58KB
11. Deep Reinforcement Learning (Theory)/14. How to Learn Reinforcement Learning.mp4
37.5MB
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11. Deep Reinforcement Learning (Theory)/14. How to Learn Reinforcement Learning.vtt
6.72KB
11. Deep Reinforcement Learning (Theory)/2. Elements of a Reinforcement Learning Problem.mp4
97.78MB
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11. Deep Reinforcement Learning (Theory)/2. Elements of a Reinforcement Learning Problem.vtt
22.86KB
11. Deep Reinforcement Learning (Theory)/3. States, Actions, Rewards, Policies.mp4
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11. Deep Reinforcement Learning (Theory)/3. States, Actions, Rewards, Policies.vtt
10KB
11. Deep Reinforcement Learning (Theory)/4. Markov Decision Processes (MDPs).mp4
48.95MB
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11. Deep Reinforcement Learning (Theory)/4. Markov Decision Processes (MDPs).vtt
11.19KB
11. Deep Reinforcement Learning (Theory)/5. The Return.mp4
20.94MB
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11. Deep Reinforcement Learning (Theory)/5. The Return.vtt
5.48KB
11. Deep Reinforcement Learning (Theory)/6. Value Functions and the Bellman Equation.mp4
43.28MB
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11. Deep Reinforcement Learning (Theory)/6. Value Functions and the Bellman Equation.vtt
10.91KB
11. Deep Reinforcement Learning (Theory)/7. What does it mean to “learn”.mp4
30.35MB
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10.75KB
14. Low-Level Tensorflow/2. Constants and Basic Computation.mp4
50.23MB
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8.27KB
14. Low-Level Tensorflow/3. Variables and Gradient Tape.mp4
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11.72KB
14. Low-Level Tensorflow/4. Build Your Own Custom Model.mp4
70.18MB
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14. Low-Level Tensorflow/4. Build Your Own Custom Model.vtt
11.63KB
15. In-Depth Loss Functions/1. Mean Squared Error.mp4
37.34MB
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9.86KB
15. In-Depth Loss Functions/2. Binary Cross Entropy.mp4
21.5MB
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15. In-Depth Loss Functions/2. Binary Cross Entropy.vtt
6.36KB
15. In-Depth Loss Functions/3. Categorical Cross Entropy.mp4
35.43MB
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8.45KB
16. In-Depth Gradient Descent/1. Gradient Descent.mp4
35.54MB
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16. In-Depth Gradient Descent/1. Gradient Descent.vtt
8.57KB
16. In-Depth Gradient Descent/2. Stochastic Gradient Descent.mp4
25.04MB
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16. In-Depth Gradient Descent/2. Stochastic Gradient Descent.vtt
4.76KB
16. In-Depth Gradient Descent/3. Momentum.mp4
39.35MB
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16. In-Depth Gradient Descent/3. Momentum.vtt
6.9KB
16. In-Depth Gradient Descent/4. Variable and Adaptive Learning Rates.mp4
38.52MB
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16. In-Depth Gradient Descent/4. Variable and Adaptive Learning Rates.vtt
13.3KB
16. In-Depth Gradient Descent/5. Adam.mp4
42.57MB
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16. In-Depth Gradient Descent/5. Adam.vtt
11.94KB
17. Extras/1. Links to TF2.0 Notebooks.html
7.83KB
18. Appendix FAQ/1. What is the Appendix.mp4
18.04MB
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18. Appendix FAQ/1. What is the Appendix.vtt
3.29KB
18. Appendix FAQ/10. What order should I take your courses in (part 1).mp4
88.14MB
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18. Appendix FAQ/10. What order should I take your courses in (part 1).vtt
14.17KB
18. Appendix FAQ/11. What order should I take your courses in (part 2).mp4
122.64MB
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18. Appendix FAQ/11. What order should I take your courses in (part 2).vtt
20.24KB
18. Appendix FAQ/12. Bonus Where to get discount coupons and FREE deep learning material.mp4
13.29MB
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18. Appendix FAQ/12. Bonus Where to get discount coupons and FREE deep learning material.vtt
2.91KB
18. Appendix FAQ/2. Windows-Focused Environment Setup 2018.mp4
193.99MB
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18. Appendix FAQ/2. Windows-Focused Environment Setup 2018.vtt
17.33KB
18. Appendix FAQ/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4
166.72MB
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18. Appendix FAQ/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt
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18. Appendix FAQ/4. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4
117.07MB
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18. Appendix FAQ/4. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt
27.68KB
18. Appendix FAQ/5. How to Code Yourself (part 1).mp4
82.12MB
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18. Appendix FAQ/6. How to Code Yourself (part 2).mp4
56.41MB
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18. Appendix FAQ/6. How to Code Yourself (part 2).vtt
11.44KB
18. Appendix FAQ/7. Proof that using Jupyter Notebook is the same as not using it.mp4
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18. Appendix FAQ/7. Proof that using Jupyter Notebook is the same as not using it.vtt
12.31KB
18. Appendix FAQ/8. How to Succeed in this Course (Long Version).mp4
38.92MB
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12.83KB
18. Appendix FAQ/9. Is Theano Dead.mp4
44.38MB
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18. Appendix FAQ/9. Is Theano Dead.vtt
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2. Google Colab/1. Intro to Google Colab, how to use a GPU or TPU for free.mp4
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2. Google Colab/1. Intro to Google Colab, how to use a GPU or TPU for free.vtt
12.37KB
2. Google Colab/2. Tensorflow 2.0 in Google Colab.mp4
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2. Google Colab/3. Uploading your own data to Google Colab.mp4
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2. Google Colab/4. Where can I learn about Numpy, Scipy, Matplotlib, Pandas, and Scikit-Learn.mp4
43.85MB
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3. Machine Learning and Neurons/1. What is Machine Learning.mp4
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3. Machine Learning and Neurons/2. Code Preparation (Classification Theory).mp4
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3. Machine Learning and Neurons/3. Classification Notebook.mp4
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3. Machine Learning and Neurons/6. The Neuron.mp4
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3. Machine Learning and Neurons/6. The Neuron.vtt
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3. Machine Learning and Neurons/7. How does a model learn.mp4
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5. Convolutional Neural Networks/1. What is Convolution (part 1).mp4
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5. Convolutional Neural Networks/11. Improving CIFAR-10 Results.mp4
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5. Convolutional Neural Networks/4. Convolution on Color Images.mp4
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5. Convolutional Neural Networks/4. Convolution on Color Images.vtt
18.04KB
5. Convolutional Neural Networks/5. CNN Architecture.mp4
90.94MB
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5. Convolutional Neural Networks/5. CNN Architecture.vtt
24.4KB
5. Convolutional Neural Networks/6. CNN Code Preparation.mp4
86.3MB
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5. Convolutional Neural Networks/6. CNN Code Preparation.vtt
17.18KB
5. Convolutional Neural Networks/7. CNN for Fashion MNIST.mp4
51.65MB
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7KB
5. Convolutional Neural Networks/8. CNN for CIFAR-10.mp4
34.8MB
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4.74KB
5. Convolutional Neural Networks/9. Data Augmentation.mp4
39.16MB
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9.83KB
6. Recurrent Neural Networks, Time Series, and Sequence Data/1. Sequence Data.mp4
103.19MB
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20.94KB
6. Recurrent Neural Networks, Time Series, and Sequence Data/10. GRU and LSTM (pt 2).mp4
53.58MB
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6. Recurrent Neural Networks, Time Series, and Sequence Data/10. GRU and LSTM (pt 2).vtt
12.73KB
6. Recurrent Neural Networks, Time Series, and Sequence Data/11. A More Challenging Sequence.mp4
77.66MB
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6. Recurrent Neural Networks, Time Series, and Sequence Data/12. Demo of the Long Distance Problem.mp4
143.12MB
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20.07KB
6. Recurrent Neural Networks, Time Series, and Sequence Data/13. RNN for Image Classification (Theory).mp4
31.5MB
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6. Recurrent Neural Networks, Time Series, and Sequence Data/14. RNN for Image Classification (Code).mp4
27.44MB
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6. Recurrent Neural Networks, Time Series, and Sequence Data/14. RNN for Image Classification (Code).vtt
3.66KB
6. Recurrent Neural Networks, Time Series, and Sequence Data/15. Stock Return Predictions using LSTMs (pt 1).mp4
80.04MB
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6. Recurrent Neural Networks, Time Series, and Sequence Data/15. Stock Return Predictions using LSTMs (pt 1).vtt
13.69KB
6. Recurrent Neural Networks, Time Series, and Sequence Data/16. Stock Return Predictions using LSTMs (pt 2).mp4
38.19MB
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6. Recurrent Neural Networks, Time Series, and Sequence Data/16. Stock Return Predictions using LSTMs (pt 2).vtt
5.65KB
6. Recurrent Neural Networks, Time Series, and Sequence Data/17. Stock Return Predictions using LSTMs (pt 3).mp4
76.74MB
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6. Recurrent Neural Networks, Time Series, and Sequence Data/17. Stock Return Predictions using LSTMs (pt 3).vtt
12.62KB
6. Recurrent Neural Networks, Time Series, and Sequence Data/2. Forecasting.mp4
47.24MB
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11.12KB
6. Recurrent Neural Networks, Time Series, and Sequence Data/3. Autoregressive Linear Model for Time Series Prediction.mp4
87.68MB
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12.39KB
6. Recurrent Neural Networks, Time Series, and Sequence Data/4. Proof that the Linear Model Works.mp4
18.27MB
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76.09MB
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18.38KB
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57.96MB
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14.16KB
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62.93MB
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14.73KB
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36.14MB
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5.38KB
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60.56MB
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8.55KB
7. Natural Language Processing (NLP)/5. CNNs for Text.mp4
40.86MB
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8.42KB
7. Natural Language Processing (NLP)/6. Text Classification with CNNs.mp4
46.4MB
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5.78KB
8. Recommender Systems/1. Recommender Systems with Deep Learning Theory.mp4
68.73MB
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15.16KB
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58.79MB
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10.27KB
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55.15MB
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9.4KB
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31.55MB
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6.44KB
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36.56MB
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7.74KB
9. Transfer Learning for Computer Vision/4. 2 Approaches to Transfer Learning.mp4
20.62MB
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9. Transfer Learning for Computer Vision/4. 2 Approaches to Transfer Learning.vtt
5.25KB
9. Transfer Learning for Computer Vision/5. Transfer Learning Code (pt 1).mp4
66.57MB
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9. Transfer Learning for Computer Vision/5. Transfer Learning Code (pt 1).vtt
12.08KB
9. Transfer Learning for Computer Vision/6. Transfer Learning Code (pt 2).mp4
46.06MB
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9. Transfer Learning for Computer Vision/6. Transfer Learning Code (pt 2).vtt
9.15KB
[CourseClub.Me].url
48B
[DesireCourse.Net].url
51B

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