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[PaidCoursesForFree.com] - Udemy - Applied Deep Learning Build a Chatbot - Theory, Application

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File Name
Size
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
1.0 kB
1. Theory Part 1 - RNNs and LSTMs/7. LSTM Variants.vtt
3.9 kB
1. Theory Part 1 - RNNs and LSTMs/8. LSTM Step-by-Step Example Walktrough.vtt
4.6 kB
5. Practical Part 3 - Data Preperation/2. Understanding the zip function.vtt
6.4 kB
6. Practical Part 4 - Building the Model/1. Understanding the Encoder.vtt
6.8 kB
2. Theory Part 2 - Sequence Modeling/2. Attention Mechanisms.vtt
7.1 kB
7. Practical Part 5 - Training the Model/2. Teacher Forcing.vtt
7.3 kB
7. Practical Part 5 - Training the Model/1. Creating the Loss Function.vtt
7.4 kB
4. Practical Part 2 - Processing the Dataset/5. Processing the Dataset Part 4.vtt
7.5 kB
4. Practical Part 2 - Processing the Dataset/2. Processing the Dataset Part 1.vtt
7.6 kB
4. Practical Part 2 - Processing the Dataset/9. Filtering the Text.vtt
7.8 kB
2. Theory Part 2 - Sequence Modeling/3. How Attention Mechanisms Work.vtt
8.1 kB
6. Practical Part 4 - Building the Model/3. Understanding Pack Padded Sequence.vtt
8.4 kB
4. Practical Part 2 - Processing the Dataset/3. Processing the Data Part 2.vtt
9.3 kB
5. Practical Part 3 - Data Preperation/3. Preparing the Data for Model Part 2.vtt
9.3 kB
1. Theory Part 1 - RNNs and LSTMs/3. Introduction to RNNs Part 2.vtt
9.9 kB
4. Practical Part 2 - Processing the Dataset/8. Processing the Text Part 2.vtt
10 kB
4. Practical Part 2 - Processing the Dataset/4. Processing the Dataset Part 3.vtt
10 kB
2. Theory Part 2 - Sequence Modeling/1. Sequence-to-Sequence Models.vtt
10 kB
4. Practical Part 2 - Processing the Dataset/10. Getting Rid of Rare Words.vtt
10 kB
1. Theory Part 1 - RNNs and LSTMs/6. LSTMs.vtt
11 kB
1. Theory Part 1 - RNNs and LSTMs/5. Playing with the Activations.vtt
11 kB
4. Practical Part 2 - Processing the Dataset/7. Processing the Text.vtt
11 kB
4. Practical Part 2 - Processing the Dataset/1. The Dataset.vtt
11 kB
5. Practical Part 3 - Data Preperation/4. Preparing the Data for Model Part 3.vtt
12 kB
3. Practical Part 1 - Introduction to PyTorch/1. Installing PyTorch and an Introduction.vtt
13 kB
1. Theory Part 1 - RNNs and LSTMs/2. Introduction to RNNs Part 1.vtt
13 kB
7. Practical Part 5 - Training the Model/4. Visualize Training Part 2.vtt
13 kB
3. Practical Part 1 - Introduction to PyTorch/2. Torch Tensors Part 1.vtt
13 kB
4. Practical Part 2 - Processing the Dataset/6. Processing the Words.vtt
14 kB
5. Practical Part 3 - Data Preperation/1. Preparing the Data for Model Part 1.vtt
14 kB
7. Practical Part 5 - Training the Model/5. Training.vtt
14 kB
5. Practical Part 3 - Data Preperation/5. Preparing the Data for Model Part 4.vtt
15 kB
7. Practical Part 5 - Training the Model/3. Visualize Training Part 1.vtt
16 kB
6. Practical Part 4 - Building the Model/5. Designing the Decoder Part 1.vtt
17 kB
6. Practical Part 4 - Building the Model/4. Designing the Attention Model.vtt
18 kB
6. Practical Part 4 - Building the Model/6. Designing the Decoder Part 2.vtt
20 kB
6. Practical Part 4 - Building the Model/2. Defining the Encoder.vtt
28 kB
1. Theory Part 1 - RNNs and LSTMs/8. LSTM Step-by-Step Example Walktrough.mp4
23 MB
1. Theory Part 1 - RNNs and LSTMs/7. LSTM Variants.mp4
24 MB
2. Theory Part 2 - Sequence Modeling/3. How Attention Mechanisms Work.mp4
37 MB
2. Theory Part 2 - Sequence Modeling/2. Attention Mechanisms.mp4
40 MB
2. Theory Part 2 - Sequence Modeling/1. Sequence-to-Sequence Models.mp4
44 MB
5. Practical Part 3 - Data Preperation/2. Understanding the zip function.mp4
45 MB
7. Practical Part 5 - Training the Model/2. Teacher Forcing.mp4
49 MB
6. Practical Part 4 - Building the Model/1. Understanding the Encoder.mp4
53 MB
5. Practical Part 3 - Data Preperation/3. Preparing the Data for Model Part 2.mp4
55 MB
4. Practical Part 2 - Processing the Dataset/5. Processing the Dataset Part 4.mp4
56 MB
6. Practical Part 4 - Building the Model/3. Understanding Pack Padded Sequence.mp4
59 MB
4. Practical Part 2 - Processing the Dataset/9. Filtering the Text.mp4
63 MB
1. Theory Part 1 - RNNs and LSTMs/6. LSTMs.mp4
67 MB
7. Practical Part 5 - Training the Model/1. Creating the Loss Function.mp4
68 MB
1. Theory Part 1 - RNNs and LSTMs/3. Introduction to RNNs Part 2.mp4
68 MB
3. Practical Part 1 - Introduction to PyTorch/3. Torch Tensors Part 2.mp4
68 MB
3. Practical Part 1 - Introduction to PyTorch/3. Torch Tensors Part 2.vtt
68 MB
4. Practical Part 2 - Processing the Dataset/2. Processing the Dataset Part 1.mp4
68 MB
1. Theory Part 1 - RNNs and LSTMs/5. Playing with the Activations.mp4
72 MB
3. Practical Part 1 - Introduction to PyTorch/1. Installing PyTorch and an Introduction.mp4
73 MB
4. Practical Part 2 - Processing the Dataset/3. Processing the Data Part 2.mp4
74 MB
4. Practical Part 2 - Processing the Dataset/4. Processing the Dataset Part 3.mp4
76 MB
3. Practical Part 1 - Introduction to PyTorch/2. Torch Tensors Part 1.mp4
78 MB
1. Theory Part 1 - RNNs and LSTMs/2. Introduction to RNNs Part 1.mp4
79 MB
4. Practical Part 2 - Processing the Dataset/1. The Dataset.mp4
82 MB
4. Practical Part 2 - Processing the Dataset/10. Getting Rid of Rare Words.mp4
82 MB
5. Practical Part 3 - Data Preperation/1. Preparing the Data for Model Part 1.mp4
87 MB
5. Practical Part 3 - Data Preperation/4. Preparing the Data for Model Part 3.mp4
89 MB
4. Practical Part 2 - Processing the Dataset/6. Processing the Words.mp4
89 MB
4. Practical Part 2 - Processing the Dataset/7. Processing the Text.mp4
96 MB
4. Practical Part 2 - Processing the Dataset/8. Processing the Text Part 2.mp4
96 MB
5. Practical Part 3 - Data Preperation/5. Preparing the Data for Model Part 4.mp4
104 MB
7. Practical Part 5 - Training the Model/4. Visualize Training Part 2.mp4
113 MB
7. Practical Part 5 - Training the Model/5. Training.mp4
123 MB
6. Practical Part 4 - Building the Model/5. Designing the Decoder Part 1.mp4
127 MB
7. Practical Part 5 - Training the Model/3. Visualize Training Part 1.mp4
132 MB
6. Practical Part 4 - Building the Model/4. Designing the Attention Model.mp4
152 MB
6. Practical Part 4 - Building the Model/6. Designing the Decoder Part 2.mp4
160 MB
6. Practical Part 4 - Building the Model/2. Defining the Encoder.mp4
242 MB