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[PaidCoursesForFree.com] - Udemy - Applied Deep Learning Build a Chatbot - Theory, Application
magnet:?xt=urn:btih:3d7c30874d0b0bf65059dfc7af6382eca800db44&dn=[PaidCoursesForFree.com] - Udemy - Applied Deep Learning Build a Chatbot - Theory, Application
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Hash值:
3d7c30874d0b0bf65059dfc7af6382eca800db44
点击数:
279
文件大小:
3.04 GB
文件数量:
38
创建日期:
2020-8-4 01:54
最后访问:
2024-6-28 05:18
访问标签:
PaidCoursesForFree
com
-
Udemy
-
Applied
Deep
Learning
Build
a
Chatbot
-
Theory
Application
文件列表详情
1. Theory Part 1 - RNNs and LSTMs/8. LSTM Step-by-Step Example Walktrough.mp4 22.76 MB
1. Theory Part 1 - RNNs and LSTMs/7. LSTM Variants.mp4 23.5 MB
2. Theory Part 2 - Sequence Modeling/3. How Attention Mechanisms Work.mp4 36.78 MB
2. Theory Part 2 - Sequence Modeling/2. Attention Mechanisms.mp4 40.13 MB
2. Theory Part 2 - Sequence Modeling/1. Sequence-to-Sequence Models.mp4 43.57 MB
5. Practical Part 3 - Data Preperation/2. Understanding the zip function.mp4 45.38 MB
7. Practical Part 5 - Training the Model/2. Teacher Forcing.mp4 48.89 MB
6. Practical Part 4 - Building the Model/1. Understanding the Encoder.mp4 53.23 MB
5. Practical Part 3 - Data Preperation/3. Preparing the Data for Model Part 2.mp4 54.96 MB
4. Practical Part 2 - Processing the Dataset/5. Processing the Dataset Part 4.mp4 56.17 MB
6. Practical Part 4 - Building the Model/3. Understanding Pack Padded Sequence.mp4 59.14 MB
4. Practical Part 2 - Processing the Dataset/9. Filtering the Text.mp4 63.23 MB
1. Theory Part 1 - RNNs and LSTMs/6. LSTMs.mp4 66.69 MB
7. Practical Part 5 - Training the Model/1. Creating the Loss Function.mp4 67.47 MB
1. Theory Part 1 - RNNs and LSTMs/3. Introduction to RNNs Part 2.mp4 67.84 MB
3. Practical Part 1 - Introduction to PyTorch/3. Torch Tensors Part 2.mp4 67.95 MB
4. Practical Part 2 - Processing the Dataset/2. Processing the Dataset Part 1.mp4 68.07 MB
1. Theory Part 1 - RNNs and LSTMs/5. Playing with the Activations.mp4 71.58 MB
3. Practical Part 1 - Introduction to PyTorch/1. Installing PyTorch and an Introduction.mp4 72.93 MB
4. Practical Part 2 - Processing the Dataset/3. Processing the Data Part 2.mp4 73.84 MB
4. Practical Part 2 - Processing the Dataset/4. Processing the Dataset Part 3.mp4 75.69 MB
3. Practical Part 1 - Introduction to PyTorch/2. Torch Tensors Part 1.mp4 77.7 MB
1. Theory Part 1 - RNNs and LSTMs/2. Introduction to RNNs Part 1.mp4 79.41 MB
4. Practical Part 2 - Processing the Dataset/1. The Dataset.mp4 81.85 MB
4. Practical Part 2 - Processing the Dataset/10. Getting Rid of Rare Words.mp4 82.54 MB
5. Practical Part 3 - Data Preperation/1. Preparing the Data for Model Part 1.mp4 87.1 MB
5. Practical Part 3 - Data Preperation/4. Preparing the Data for Model Part 3.mp4 88.57 MB
4. Practical Part 2 - Processing the Dataset/6. Processing the Words.mp4 89.21 MB
4. Practical Part 2 - Processing the Dataset/7. Processing the Text.mp4 95.63 MB
4. Practical Part 2 - Processing the Dataset/8. Processing the Text Part 2.mp4 95.63 MB
5. Practical Part 3 - Data Preperation/5. Preparing the Data for Model Part 4.mp4 104.29 MB
7. Practical Part 5 - Training the Model/4. Visualize Training Part 2.mp4 113.13 MB
7. Practical Part 5 - Training the Model/5. Training.mp4 122.86 MB
6. Practical Part 4 - Building the Model/5. Designing the Decoder Part 1.mp4 127.27 MB
7. Practical Part 5 - Training the Model/3. Visualize Training Part 1.mp4 131.88 MB
6. Practical Part 4 - Building the Model/4. Designing the Attention Model.mp4 151.49 MB
6. Practical Part 4 - Building the Model/6. Designing the Decoder Part 2.mp4 160.16 MB
6. Practical Part 4 - Building the Model/2. Defining the Encoder.mp4 242.23 MB
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