[PaidCoursesForFree.com] - Udemy - Applied Deep Learning Build a Chatbot - Theory, Application
大小
3.1 GB
文件数
80
Info Hash:
3D7C30874D0B0BF65059DFC7AF6382ECA800DB44
收录时间
2026-01-04 08:07:41
更新时间
2026-01-04 08:07:41
文件列表 (80)
PaidCoursesForFree.com.url
121 B
1. Theory Part 1 - RNNs and LSTMs/4. Test Your Understanding.html
160 B
7. Practical Part 5 - Training the Model/6. Proceeding.html
384 B
1. Theory Part 1 - RNNs and LSTMs/1. Before we Start.html
1.04 KB
1. Theory Part 1 - RNNs and LSTMs/7. LSTM Variants.vtt
3.91 KB
1. Theory Part 1 - RNNs and LSTMs/8. LSTM Step-by-Step Example Walktrough.vtt
4.57 KB
5. Practical Part 3 - Data Preperation/2. Understanding the zip function.vtt
6.37 KB
6. Practical Part 4 - Building the Model/1. Understanding the Encoder.vtt
6.82 KB
2. Theory Part 2 - Sequence Modeling/2. Attention Mechanisms.vtt
7.12 KB
7. Practical Part 5 - Training the Model/2. Teacher Forcing.vtt
7.28 KB
7. Practical Part 5 - Training the Model/1. Creating the Loss Function.vtt
7.44 KB
4. Practical Part 2 - Processing the Dataset/5. Processing the Dataset Part 4.vtt
7.53 KB
4. Practical Part 2 - Processing the Dataset/2. Processing the Dataset Part 1.vtt
7.59 KB
4. Practical Part 2 - Processing the Dataset/9. Filtering the Text.vtt
7.81 KB
2. Theory Part 2 - Sequence Modeling/3. How Attention Mechanisms Work.vtt
8.14 KB
6. Practical Part 4 - Building the Model/3. Understanding Pack Padded Sequence.vtt
8.36 KB
4. Practical Part 2 - Processing the Dataset/3. Processing the Data Part 2.vtt
9.27 KB
5. Practical Part 3 - Data Preperation/3. Preparing the Data for Model Part 2.vtt
9.28 KB
1. Theory Part 1 - RNNs and LSTMs/3. Introduction to RNNs Part 2.vtt
9.86 KB
4. Practical Part 2 - Processing the Dataset/8. Processing the Text Part 2.vtt
10.08 KB
4. Practical Part 2 - Processing the Dataset/4. Processing the Dataset Part 3.vtt
10.22 KB
2. Theory Part 2 - Sequence Modeling/1. Sequence-to-Sequence Models.vtt
10.3 KB
4. Practical Part 2 - Processing the Dataset/10. Getting Rid of Rare Words.vtt
10.3 KB
1. Theory Part 1 - RNNs and LSTMs/6. LSTMs.vtt
10.69 KB
1. Theory Part 1 - RNNs and LSTMs/5. Playing with the Activations.vtt
10.85 KB
4. Practical Part 2 - Processing the Dataset/7. Processing the Text.vtt
10.87 KB
4. Practical Part 2 - Processing the Dataset/1. The Dataset.vtt
11.17 KB
5. Practical Part 3 - Data Preperation/4. Preparing the Data for Model Part 3.vtt
12.2 KB
3. Practical Part 1 - Introduction to PyTorch/1. Installing PyTorch and an Introduction.vtt
12.64 KB
1. Theory Part 1 - RNNs and LSTMs/2. Introduction to RNNs Part 1.vtt
12.66 KB
7. Practical Part 5 - Training the Model/4. Visualize Training Part 2.vtt
12.66 KB
3. Practical Part 1 - Introduction to PyTorch/2. Torch Tensors Part 1.vtt
13.21 KB
4. Practical Part 2 - Processing the Dataset/6. Processing the Words.vtt
13.56 KB
5. Practical Part 3 - Data Preperation/1. Preparing the Data for Model Part 1.vtt
14.21 KB
7. Practical Part 5 - Training the Model/5. Training.vtt
14.36 KB
5. Practical Part 3 - Data Preperation/5. Preparing the Data for Model Part 4.vtt
15.18 KB
7. Practical Part 5 - Training the Model/3. Visualize Training Part 1.vtt
16.41 KB
6. Practical Part 4 - Building the Model/5. Designing the Decoder Part 1.vtt
16.67 KB
6. Practical Part 4 - Building the Model/4. Designing the Attention Model.vtt
18.3 KB
6. Practical Part 4 - Building the Model/6. Designing the Decoder Part 2.vtt
20.38 KB
6. Practical Part 4 - Building the Model/2. Defining the Encoder.vtt
28.05 KB
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
3. Practical Part 1 - Introduction to PyTorch/3. Torch Tensors Part 2.vtt
67.96 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