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[GigaCourse.Com] Udemy - Tensorflow 2.0 Deep Learning and Artificial Intelligence
magnet:?xt=urn:btih:d70b1933126900588bd11838743cc21140d2526a&dn=[GigaCourse.Com] Udemy - Tensorflow 2.0 Deep Learning and Artificial Intelligence
磁力链接详情
Hash值:
d70b1933126900588bd11838743cc21140d2526a
点击数:
60
文件大小:
6.83 GB
文件数量:
133
创建日期:
2023-6-15 13:28
最后访问:
2024-5-19 06:57
访问标签:
GigaCourse
Com
Udemy
-
Tensorflow
2
0
Deep
Learning
and
Artificial
Intelligence
文件列表详情
1. Welcome/1. Introduction.mp4 34.81 MB
1. Welcome/2. Outline.mp4 73.67 MB
1. Welcome/3. Where to get the code.mp4 62.91 MB
10. GANs (Generative Adversarial Networks)/1. GAN Theory.mp4 87.16 MB
10. GANs (Generative Adversarial Networks)/2. GAN Code.mp4 78.3 MB
11. Deep Reinforcement Learning (Theory)/1. Deep Reinforcement Learning Section Introduction.mp4 38.05 MB
11. Deep Reinforcement Learning (Theory)/10. Epsilon-Greedy.mp4 40.11 MB
11. Deep Reinforcement Learning (Theory)/11. Q-Learning.mp4 61.83 MB
11. Deep Reinforcement Learning (Theory)/12. Deep Q-Learning DQN (pt 1).mp4 56.27 MB
11. Deep Reinforcement Learning (Theory)/13. Deep Q-Learning DQN (pt 2).mp4 49.6 MB
11. Deep Reinforcement Learning (Theory)/14. How to Learn Reinforcement Learning.mp4 37.7 MB
11. Deep Reinforcement Learning (Theory)/2. Elements of a Reinforcement Learning Problem.mp4 98.59 MB
11. Deep Reinforcement Learning (Theory)/3. States, Actions, Rewards, Policies.mp4 43.33 MB
11. Deep Reinforcement Learning (Theory)/4. Markov Decision Processes (MDPs).mp4 49.35 MB
11. Deep Reinforcement Learning (Theory)/5. The Return.mp4 21.13 MB
11. Deep Reinforcement Learning (Theory)/6. Value Functions and the Bellman Equation.mp4 43.56 MB
11. Deep Reinforcement Learning (Theory)/7. What does it mean to “learn”.mp4 31.71 MB
11. Deep Reinforcement Learning (Theory)/8. Solving the Bellman Equation with Reinforcement Learning (pt 1).mp4 42.74 MB
11. Deep Reinforcement Learning (Theory)/9. Solving the Bellman Equation with Reinforcement Learning (pt 2).mp4 52.91 MB
12. Stock Trading Project with Deep Reinforcement Learning/1. Reinforcement Learning Stock Trader Introduction.mp4 26.04 MB
12. Stock Trading Project with Deep Reinforcement Learning/10. Help! Why is the code slower on my machine.mp4 42.46 MB
12. Stock Trading Project with Deep Reinforcement Learning/2. Data and Environment.mp4 50.97 MB
12. Stock Trading Project with Deep Reinforcement Learning/3. Replay Buffer.mp4 24.04 MB
12. Stock Trading Project with Deep Reinforcement Learning/4. Program Design and Layout.mp4 25.98 MB
12. Stock Trading Project with Deep Reinforcement Learning/5. Code pt 1.mp4 39.55 MB
12. Stock Trading Project with Deep Reinforcement Learning/6. Code pt 2.mp4 68 MB
12. Stock Trading Project with Deep Reinforcement Learning/7. Code pt 3.mp4 52.05 MB
12. Stock Trading Project with Deep Reinforcement Learning/8. Code pt 4.mp4 52.51 MB
12. Stock Trading Project with Deep Reinforcement Learning/9. Reinforcement Learning Stock Trader Discussion.mp4 16.59 MB
13. Advanced Tensorflow Usage/1. What is a Web Service (Tensorflow Serving pt 1).mp4 27.78 MB
13. Advanced Tensorflow Usage/2. Tensorflow Serving pt 2.mp4 104.99 MB
13. Advanced Tensorflow Usage/3. Tensorflow Lite (TFLite).mp4 42.59 MB
13. Advanced Tensorflow Usage/4. Why is Google the King of Distributed Computing.mp4 44.93 MB
13. Advanced Tensorflow Usage/5. Training with Distributed Strategies.mp4 43.54 MB
13. Advanced Tensorflow Usage/6. Using the TPU.mp4 45.24 MB
14. Low-Level Tensorflow/1. Differences Between Tensorflow 1.x and Tensorflow 2.x.mp4 38.68 MB
14. Low-Level Tensorflow/2. Constants and Basic Computation.mp4 40.3 MB
14. Low-Level Tensorflow/3. Variables and Gradient Tape.mp4 56.05 MB
14. Low-Level Tensorflow/4. Build Your Own Custom Model.mp4 58.55 MB
15. In-Depth Loss Functions/1. Mean Squared Error.mp4 33.77 MB
15. In-Depth Loss Functions/2. Binary Cross Entropy.mp4 23.68 MB
15. In-Depth Loss Functions/3. Categorical Cross Entropy.mp4 31.7 MB
16. In-Depth Gradient Descent/1. Gradient Descent.mp4 34.92 MB
16. In-Depth Gradient Descent/2. Stochastic Gradient Descent.mp4 22.97 MB
16. In-Depth Gradient Descent/3. Momentum.mp4 34.25 MB
16. In-Depth Gradient Descent/4. Variable and Adaptive Learning Rates.mp4 34.85 MB
16. In-Depth Gradient Descent/5. Adam (pt 1).mp4 55.12 MB
16. In-Depth Gradient Descent/6. Adam (pt 2).mp4 52.76 MB
17. Extras/1. How to Choose Hyperparameters.mp4 37.92 MB
17. Extras/2. Where Are The Exercises.mp4 25.98 MB
18. Setting up your Environment (FAQ by Student Request)/1. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 150.59 MB
18. Setting up your Environment (FAQ by Student Request)/2. Anaconda Environment Setup.mp4 180.9 MB
18. Setting up your Environment (FAQ by Student Request)/3. Installing NVIDIA GPU-Accelerated Deep Learning Libraries on your Home Computer.mp4 167.3 MB
19. Extra Help With Python Coding for Beginners (FAQ by Student Request)/1. Beginner's Coding Tips.mp4 75.71 MB
19. Extra Help With Python Coding for Beginners (FAQ by Student Request)/2. How to Code Yourself (part 1).mp4 71.85 MB
19. Extra Help With Python Coding for Beginners (FAQ by Student Request)/3. How to Code Yourself (part 2).mp4 49.14 MB
19. Extra Help With Python Coding for Beginners (FAQ by Student Request)/4. Proof that using Jupyter Notebook is the same as not using it.mp4 69.45 MB
19. Extra Help With Python Coding for Beginners (FAQ by Student Request)/5. Is Theano Dead.mp4 40.76 MB
2. Google Colab/1. Intro to Google Colab, how to use a GPU or TPU for free.mp4 53.84 MB
2. Google Colab/2. Tensorflow 2.0 in Google Colab.mp4 40.65 MB
2. Google Colab/3. Uploading your own data to Google Colab.mp4 73.59 MB
2. Google Colab/4. Where can I learn about Numpy, Scipy, Matplotlib, Pandas, and Scikit-Learn.mp4 38.93 MB
2. Google Colab/5. How to Succeed in this Course.mp4 43.75 MB
20. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/1. How to Succeed in this Course (Long Version).mp4 35.22 MB
20. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 105.61 MB
20. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 79.71 MB
20. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 108.17 MB
21. Appendix FAQ Finale/1. What is the Appendix.mp4 16.38 MB
21. Appendix FAQ Finale/2. BONUS Lecture.mp4 37.79 MB
3. Machine Learning and Neurons/1. What is Machine Learning.mp4 65.5 MB
3. Machine Learning and Neurons/10. Why Keras.mp4 26.51 MB
3. Machine Learning and Neurons/11. Suggestion Box.mp4 27.12 MB
3. Machine Learning and Neurons/2. Code Preparation (Classification Theory).mp4 59.8 MB
3. Machine Learning and Neurons/3. Classification Notebook.mp4 54.54 MB
3. Machine Learning and Neurons/4. Code Preparation (Regression Theory).mp4 27.29 MB
3. Machine Learning and Neurons/5. Regression Notebook.mp4 57.47 MB
3. Machine Learning and Neurons/6. The Neuron.mp4 42.57 MB
3. Machine Learning and Neurons/7. How does a model learn.mp4 47.95 MB
3. Machine Learning and Neurons/8. Making Predictions.mp4 33.88 MB
3. Machine Learning and Neurons/9. Saving and Loading a Model.mp4 29.73 MB
4. Feedforward Artificial Neural Networks/1. Artificial Neural Networks Section Introduction.mp4 29.82 MB
4. Feedforward Artificial Neural Networks/10. ANN for Regression.mp4 69.27 MB
4. Feedforward Artificial Neural Networks/2. Beginners Rejoice The Math in This Course is Optional.mp4 68.52 MB
4. Feedforward Artificial Neural Networks/3. Forward Propagation.mp4 46.7 MB
4. Feedforward Artificial Neural Networks/4. The Geometrical Picture.mp4 56.43 MB
4. Feedforward Artificial Neural Networks/5. Activation Functions.mp4 80.54 MB
4. Feedforward Artificial Neural Networks/6. Multiclass Classification.mp4 41.38 MB
4. Feedforward Artificial Neural Networks/7. How to Represent Images.mp4 70.46 MB
4. Feedforward Artificial Neural Networks/8. Code Preparation (ANN).mp4 50.92 MB
4. Feedforward Artificial Neural Networks/9. ANN for Image Classification.mp4 47.71 MB
5. Convolutional Neural Networks/1. What is Convolution (part 1).mp4 79.77 MB
5. Convolutional Neural Networks/10. Batch Normalization.mp4 21.11 MB
5. Convolutional Neural Networks/11. Improving CIFAR-10 Results.mp4 72.91 MB
5. Convolutional Neural Networks/2. What is Convolution (part 2).mp4 22.27 MB
5. Convolutional Neural Networks/3. What is Convolution (part 3).mp4 27.64 MB
5. Convolutional Neural Networks/4. Convolution on Color Images.mp4 69.44 MB
5. Convolutional Neural Networks/5. CNN Architecture.mp4 80.58 MB
5. Convolutional Neural Networks/6. CNN Code Preparation.mp4 76.88 MB
5. Convolutional Neural Networks/7. CNN for Fashion MNIST.mp4 42.79 MB
5. Convolutional Neural Networks/8. CNN for CIFAR-10.mp4 29.69 MB
5. Convolutional Neural Networks/9. Data Augmentation.mp4 34.95 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/1. Sequence Data.mp4 90.15 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/10. GRU and LSTM (pt 2).mp4 50.36 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/11. A More Challenging Sequence.mp4 64.65 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/12. Demo of the Long Distance Problem.mp4 124.05 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/13. RNN for Image Classification (Theory).mp4 29.12 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/14. RNN for Image Classification (Code).mp4 23.3 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/15. Stock Return Predictions using LSTMs (pt 1).mp4 67.11 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/16. Stock Return Predictions using LSTMs (pt 2).mp4 32.97 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/17. Stock Return Predictions using LSTMs (pt 3).mp4 67.34 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/18. Other Ways to Forecast.mp4 28.33 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/2. Forecasting.mp4 46.75 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/3. Autoregressive Linear Model for Time Series Prediction.mp4 71.7 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/4. Proof that the Linear Model Works.mp4 16.2 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/5. Recurrent Neural Networks.mp4 83 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/6. RNN Code Preparation.mp4 18.43 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/7. RNN for Time Series Prediction.mp4 74.07 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/8. Paying Attention to Shapes.mp4 52.48 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/9. GRU and LSTM (pt 1).mp4 79.86 MB
7. Natural Language Processing (NLP)/1. Embeddings.mp4 52.56 MB
7. Natural Language Processing (NLP)/2. Code Preparation (NLP).mp4 57.04 MB
7. Natural Language Processing (NLP)/3. Text Preprocessing.mp4 28.76 MB
7. Natural Language Processing (NLP)/4. Text Classification with LSTMs.mp4 50.68 MB
7. Natural Language Processing (NLP)/5. CNNs for Text.mp4 40.4 MB
7. Natural Language Processing (NLP)/6. Text Classification with CNNs.mp4 39.62 MB
8. Recommender Systems/1. Recommender Systems with Deep Learning Theory.mp4 68.66 MB
8. Recommender Systems/2. Recommender Systems with Deep Learning Code.mp4 58.81 MB
9. Transfer Learning for Computer Vision/1. Transfer Learning Theory.mp4 55.13 MB
9. Transfer Learning for Computer Vision/2. Some Pre-trained Models (VGG, ResNet, Inception, MobileNet).mp4 31.57 MB
9. Transfer Learning for Computer Vision/3. Large Datasets and Data Generators.mp4 36.56 MB
9. Transfer Learning for Computer Vision/4. 2 Approaches to Transfer Learning.mp4 20.58 MB
9. Transfer Learning for Computer Vision/5. Transfer Learning Code (pt 1).mp4 66.52 MB
9. Transfer Learning for Computer Vision/6. Transfer Learning Code (pt 2).mp4 46.05 MB
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