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

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Torrent File Content (80 files)

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

121 bytes

1. Theory Part 1 - RNNs and LSTMs
4. Test Your Understanding.html -

160 bytes

7. Practical Part 5 - Training the Model
6. Proceeding.html -

384 bytes

1. Theory Part 1 - RNNs and LSTMs
1. Before we Start.html -

1.04 KB

7. LSTM Variants.vtt -

3.91 KB

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

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

2. Processing the Dataset Part 1.vtt -

7.59 KB

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. 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

5. Playing with the Activations.vtt -

10.85 KB

4. Practical Part 2 - Processing the Dataset
7. Processing the Text.vtt -

10.87 KB

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

4. Designing the Attention Model.vtt -

18.3 KB

6. Designing the Decoder Part 2.vtt -

20.38 KB

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

7. LSTM Variants.mp4 -

23.5 MB

2. Theory Part 2 - Sequence Modeling
3. How Attention Mechanisms Work.mp4 -

36.78 MB

2. Attention Mechanisms.mp4 -

40.13 MB

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

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