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[Tutorialsplanet.NET] Udemy - PyTorch Deep Learning and Artificial Intelligence
magnet:?xt=urn:btih:5553f1e5099ac69838af28dc223a4afb557cb477&dn=[Tutorialsplanet.NET] Udemy - PyTorch Deep Learning and Artificial Intelligence
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5553f1e5099ac69838af28dc223a4afb557cb477
infohash:
149
文件数量
7.34 GB
文件大小
2021-7-26 15:04
创建日期
2024-9-29 12:53
最后访问
相关分词
Tutorialsplanet
NET
Udemy
-
PyTorch
Deep
Learning
and
Artificial
Intelligence
1. Introduction/1. Welcome.mp4 35.72 MB
1. Introduction/2. Overview and Outline.mp4 79.67 MB
1. Introduction/3. Where to get the Code.mp4 29.46 MB
10. GANs (Generative Adversarial Networks)/1. GAN Theory.mp4 92.11 MB
10. GANs (Generative Adversarial Networks)/2. GAN Code Preparation.mp4 28.08 MB
10. GANs (Generative Adversarial Networks)/3. GAN Code.mp4 61.37 MB
10. GANs (Generative Adversarial Networks)/4. Exercise DCGAN (Deep Convolutional GAN).mp4 15.31 MB
11. Deep Reinforcement Learning (Theory)/1. Deep Reinforcement Learning Section Introduction.mp4 40.66 MB
11. Deep Reinforcement Learning (Theory)/10. Epsilon-Greedy.mp4 41.46 MB
11. Deep Reinforcement Learning (Theory)/11. Q-Learning.mp4 66.78 MB
11. Deep Reinforcement Learning (Theory)/12. Deep Q-Learning DQN (pt 1).mp4 60.24 MB
11. Deep Reinforcement Learning (Theory)/13. Deep Q-Learning DQN (pt 2).mp4 52.22 MB
11. Deep Reinforcement Learning (Theory)/14. How to Learn Reinforcement Learning.mp4 40.25 MB
11. Deep Reinforcement Learning (Theory)/2. Elements of a Reinforcement Learning Problem.mp4 104.93 MB
11. Deep Reinforcement Learning (Theory)/3. States, Actions, Rewards, Policies.mp4 44.13 MB
11. Deep Reinforcement Learning (Theory)/4. Markov Decision Processes (MDPs).mp4 50.51 MB
11. Deep Reinforcement Learning (Theory)/5. The Return.mp4 23.42 MB
11. Deep Reinforcement Learning (Theory)/6. Value Functions and the Bellman Equation.mp4 47.72 MB
11. Deep Reinforcement Learning (Theory)/7. What does it mean to “learn”.mp4 31.67 MB
11. Deep Reinforcement Learning (Theory)/8. Solving the Bellman Equation with Reinforcement Learning (pt 1).mp4 42.92 MB
11. Deep Reinforcement Learning (Theory)/9. Solving the Bellman Equation with Reinforcement Learning (pt 2).mp4 57.02 MB
12. Stock Trading Project with Deep Reinforcement Learning/1. Reinforcement Learning Stock Trader Introduction.mp4 28.82 MB
12. Stock Trading Project with Deep Reinforcement Learning/10. Exercise Personalized Stock Trading Bot.mp4 7.86 MB
12. Stock Trading Project with Deep Reinforcement Learning/2. Data and Environment.mp4 55.69 MB
12. Stock Trading Project with Deep Reinforcement Learning/3. Replay Buffer.mp4 24.97 MB
12. Stock Trading Project with Deep Reinforcement Learning/4. Program Design and Layout.mp4 26.87 MB
12. Stock Trading Project with Deep Reinforcement Learning/5. Code pt 1.mp4 66.33 MB
12. Stock Trading Project with Deep Reinforcement Learning/6. Code pt 2.mp4 69.98 MB
12. Stock Trading Project with Deep Reinforcement Learning/7. Code pt 3.mp4 58.59 MB
12. Stock Trading Project with Deep Reinforcement Learning/8. Code pt 4.mp4 52.61 MB
12. Stock Trading Project with Deep Reinforcement Learning/9. Reinforcement Learning Stock Trader Discussion.mp4 17.22 MB
13. VIP Uncertainty Estimation/1. Custom Loss and Estimating Prediction Uncertainty.mp4 43.55 MB
13. VIP Uncertainty Estimation/2. Estimating Prediction Uncertainty Code.mp4 42.75 MB
14. VIP Facial Recognition/1. Facial Recognition Section Introduction.mp4 24.31 MB
14. VIP Facial Recognition/10. Facial Recognition Section Summary.mp4 18.32 MB
14. VIP Facial Recognition/2. Siamese Networks.mp4 50.51 MB
14. VIP Facial Recognition/3. Code Outline.mp4 23.85 MB
14. VIP Facial Recognition/4. Loading in the data.mp4 35.06 MB
14. VIP Facial Recognition/5. Splitting the data into train and test.mp4 26.29 MB
14. VIP Facial Recognition/6. Converting the data into pairs.mp4 30.38 MB
14. VIP Facial Recognition/7. Generating Generators.mp4 32.44 MB
14. VIP Facial Recognition/8. Creating the model and loss.mp4 29.38 MB
14. VIP Facial Recognition/9. Accuracy and imbalanced classes.mp4 51.1 MB
15. In-Depth Loss Functions/1. Mean Squared Error.mp4 33.79 MB
15. In-Depth Loss Functions/2. Binary Cross Entropy.mp4 23.69 MB
15. In-Depth Loss Functions/3. Categorical Cross Entropy.mp4 31.74 MB
16. In-Depth Gradient Descent/1. Gradient Descent.mp4 34.9 MB
16. In-Depth Gradient Descent/2. Stochastic Gradient Descent.mp4 22.99 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 55.17 MB
16. In-Depth Gradient Descent/6. Adam (pt 2).mp4 52.78 MB
18. Setting up your Environment (FAQ by Student Request)/1. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 150.67 MB
18. Setting up your Environment (FAQ by Student Request)/2. Windows-Focused Environment Setup 2018.mp4 180.68 MB
18. Setting up your Environment (FAQ by Student Request)/3. Installing NVIDIA GPU-Accelerated Deep Learning Libraries on your Home Computer.mp4 167.33 MB
19. Extra Help With Python Coding for Beginners (FAQ by Student Request)/1. How to Code Yourself (part 1).mp4 71.86 MB
19. Extra Help With Python Coding for Beginners (FAQ by Student Request)/2. How to Code Yourself (part 2).mp4 49.15 MB
19. Extra Help With Python Coding for Beginners (FAQ by Student Request)/3. Proof that using Jupyter Notebook is the same as not using it.mp4 69.49 MB
2. Google Colab/1. Intro to Google Colab, how to use a GPU or TPU for free.mp4 60.46 MB
2. Google Colab/2. Uploading your own data to Google Colab.mp4 90.54 MB
2. Google Colab/3. Where can I learn about Numpy, Scipy, Matplotlib, Pandas, and Scikit-Learn.mp4 44.38 MB
20. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/1. How to Succeed in this Course (Long Version).mp4 35.26 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 0 字节
20. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 79.59 MB
20. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 108.22 MB
21. Appendix FAQ Finale/1. What is the Appendix.mp4 16.38 MB
21. Appendix FAQ Finale/2. BONUS Where to get discount coupons and FREE deep learning material.mp4 37.81 MB
3. Machine Learning and Neurons/1. What is Machine Learning.mp4 70.59 MB
3. Machine Learning and Neurons/10. Classification Notebook.mp4 78.29 MB
3. Machine Learning and Neurons/11. Exercise Predicting Diabetes Onset.mp4 12.56 MB
3. Machine Learning and Neurons/12. Saving and Loading a Model.mp4 28.83 MB
3. Machine Learning and Neurons/13. A Short Neuroscience Primer.mp4 44.65 MB
3. Machine Learning and Neurons/14. How does a model learn.mp4 50.07 MB
3. Machine Learning and Neurons/15. Model With Logits.mp4 27.32 MB
3. Machine Learning and Neurons/16. Train Sets vs. Validation Sets vs. Test Sets.mp4 52.15 MB
3. Machine Learning and Neurons/17. Suggestion Box.mp4 16.1 MB
3. Machine Learning and Neurons/2. Regression Basics.mp4 73.02 MB
3. Machine Learning and Neurons/3. Regression Code Preparation.mp4 45.54 MB
3. Machine Learning and Neurons/4. Regression Notebook.mp4 71.93 MB
3. Machine Learning and Neurons/5. Moore's Law.mp4 30.63 MB
3. Machine Learning and Neurons/6. Moore's Law Notebook.mp4 78.91 MB
3. Machine Learning and Neurons/7. Exercise Real Estate Predictions.mp4 5.58 MB
3. Machine Learning and Neurons/8. Linear Classification Basics.mp4 67.22 MB
3. Machine Learning and Neurons/9. Classification Code Preparation.mp4 26.54 MB
4. Feedforward Artificial Neural Networks/1. Artificial Neural Networks Section Introduction.mp4 33.48 MB
4. Feedforward Artificial Neural Networks/10. Exercise E. Coli Protein Localization Sites.mp4 10.46 MB
4. Feedforward Artificial Neural Networks/2. Forward Propagation.mp4 47.1 MB
4. Feedforward Artificial Neural Networks/3. The Geometrical Picture.mp4 56.42 MB
4. Feedforward Artificial Neural Networks/4. Activation Functions.mp4 89.25 MB
4. Feedforward Artificial Neural Networks/5. Multiclass Classification.mp4 48.69 MB
4. Feedforward Artificial Neural Networks/6. How to Represent Images.mp4 75.43 MB
4. Feedforward Artificial Neural Networks/7. Code Preparation (ANN).mp4 66.12 MB
4. Feedforward Artificial Neural Networks/8. ANN for Image Classification.mp4 106.32 MB
4. Feedforward Artificial Neural Networks/9. ANN for Regression.mp4 80.19 MB
5. Convolutional Neural Networks/1. What is Convolution (part 1).mp4 79.64 MB
5. Convolutional Neural Networks/10. CNN for CIFAR-10.mp4 56.71 MB
5. Convolutional Neural Networks/11. Data Augmentation.mp4 44.52 MB
5. Convolutional Neural Networks/12. Batch Normalization.mp4 23.44 MB
5. Convolutional Neural Networks/13. Improving CIFAR-10 Results.mp4 77.42 MB
5. Convolutional Neural Networks/14. Exercise Facial Expression Recognition.mp4 8.25 MB
5. Convolutional Neural Networks/2. What is Convolution (part 2).mp4 24.49 MB
5. Convolutional Neural Networks/3. What is Convolution (part 3).mp4 28.7 MB
5. Convolutional Neural Networks/4. Convolution on Color Images.mp4 76.38 MB
5. Convolutional Neural Networks/5. CNN Architecture.mp4 89.54 MB
5. Convolutional Neural Networks/6. CNN Code Preparation (part 1).mp4 76.73 MB
5. Convolutional Neural Networks/7. CNN Code Preparation (part 2).mp4 36.71 MB
5. Convolutional Neural Networks/8. CNN Code Preparation (part 3).mp4 33.69 MB
5. Convolutional Neural Networks/9. CNN for Fashion MNIST.mp4 74.45 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/1. Sequence Data.mp4 114.29 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/10. GRU and LSTM (pt 2).mp4 50.38 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/11. A More Challenging Sequence.mp4 86.68 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/12. RNN for Image Classification (Theory).mp4 32.27 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/13. RNN for Image Classification (Code).mp4 20.53 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/14. Stock Return Predictions using LSTMs (pt 1).mp4 77.82 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/15. Stock Return Predictions using LSTMs (pt 2).mp4 43.22 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/16. Stock Return Predictions using LSTMs (pt 3).mp4 71.07 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/17. Other Ways to Forecast.mp4 28.28 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/18. Exercise More Forecasting.mp4 9.06 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/2. Forecasting.mp4 48.5 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/3. Autoregressive Linear Model for Time Series Prediction.mp4 81.2 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/4. Proof that the Linear Model Works.mp4 17.92 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/5. Recurrent Neural Networks.mp4 92.6 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/6. RNN Code Preparation.mp4 55.31 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/7. RNN for Time Series Prediction.mp4 71.85 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/8. Paying Attention to Shapes.mp4 56.4 MB
6. Recurrent Neural Networks, Time Series, and Sequence Data/9. GRU and LSTM (pt 1).mp4 76.06 MB
7. Natural Language Processing (NLP)/1. Embeddings.mp4 59.98 MB
7. Natural Language Processing (NLP)/10. Exercise Sentiment Analysis.mp4 9.12 MB
7. Natural Language Processing (NLP)/2. Neural Networks with Embeddings.mp4 15.63 MB
7. Natural Language Processing (NLP)/3. Text Preprocessing (pt 1).mp4 52.3 MB
7. Natural Language Processing (NLP)/4. Text Preprocessing (pt 2).mp4 44.41 MB
7. Natural Language Processing (NLP)/5. Text Preprocessing (pt 3).mp4 47.73 MB
7. Natural Language Processing (NLP)/6. Text Classification with LSTMs.mp4 65.05 MB
7. Natural Language Processing (NLP)/7. CNNs for Text.mp4 58.54 MB
7. Natural Language Processing (NLP)/8. Text Classification with CNNs.mp4 39.33 MB
7. Natural Language Processing (NLP)/9. VIP Making Predictions with a Trained NLP Model.mp4 48.81 MB
8. Recommender Systems/1. Recommender Systems with Deep Learning Theory.mp4 64.74 MB
8. Recommender Systems/2. Recommender Systems with Deep Learning Code Preparation.mp4 40.1 MB
8. Recommender Systems/3. Recommender Systems with Deep Learning Code (pt 1).mp4 69.57 MB
8. Recommender Systems/4. Recommender Systems with Deep Learning Code (pt 2).mp4 76.88 MB
8. Recommender Systems/5. VIP Making Predictions with a Trained Recommender Model.mp4 32.75 MB
8. Recommender Systems/6. Exercise Book Recommendations.mp4 4.08 MB
9. Transfer Learning for Computer Vision/1. Transfer Learning Theory.mp4 58.19 MB
9. Transfer Learning for Computer Vision/2. Some Pre-trained Models (VGG, ResNet, Inception, MobileNet).mp4 21.67 MB
9. Transfer Learning for Computer Vision/3. Large Datasets.mp4 41.26 MB
9. Transfer Learning for Computer Vision/4. 2 Approaches to Transfer Learning.mp4 21.8 MB
9. Transfer Learning for Computer Vision/5. Transfer Learning Code (pt 1).mp4 77.78 MB
9. Transfer Learning for Computer Vision/6. Transfer Learning Code (pt 2).mp4 56.32 MB
9. Transfer Learning for Computer Vision/7. Exercise Transfer Learning.mp4 6.95 MB
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