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TORRENT DETAILS
[PaidCoursesForFree.com] - Udemy - Applied Deep Learning Build A Chatbot - Theory, Application
TORRENT SUMMARY
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Understand the Theory of how Chatbots work and implement them in Python and PyTorch!
What you’ll learn
* Understand the theory behind Sequence Modeling
* Understand the theory of how Chatbots work
* Undertand the theory of how RNNs and LSTMs work
* Get Introduced to PyTorch
* Implement a Chatbot in PyTorch
* Undertand the theory of different Sequence Modeling Applications
Requirements
* Some Basic High School Mathematics
* Some Basic Programming Knowledge
* Some basic Knowledge about Neural Networks
Description
In this course, you’ll learn the following:
* RNNs and LSTMs
* Sequence Modeling
* PyTorch
* Building a Chatbot in PyTorch
We will first cover the theoretical concepts you need to know for building a Chatbot, which include RNNs, LSTMS and Sequence Models with Attention.
Then we will introduce you to PyTorch, a very powerful and advanced deep learning Library. We will show you how to install it and how to work with it and with PyTorch Tensors.
Then we will build our Chatbot in PyTorch!
Please Note an important thing: If you don’t have prior knowledge on Neural Networks and how they work, you won’t be able to cope well with this course. Please note that this is not a Deep Learning course, it’s an Application of Deep Learning, as the course names implies (Applied Deep Learning: Build a Chatbot). The course level is Intermediate, and not Beginner. So please familiarize yourself with Neural Networks and it’s concepts before taking this course. If you are already familiar, then your ready to start this journey!
Who this course is for:
* Anybody enthusiastic about Deep Learning Applications
Source: PaidCoursesForFree.com
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FILE LIST
Filename
Size
1. Theory Part 1 - RNNs and LSTMs/1. Before we Start.html
1 KB
1. Theory Part 1 - RNNs and LSTMs/2. Introduction to RNNs Part 1.mp4
79.4 MB
1. Theory Part 1 - RNNs and LSTMs/2. Introduction to RNNs Part 1.vtt
12.7 KB
1. Theory Part 1 - RNNs and LSTMs/3. Introduction to RNNs Part 2.mp4
67.8 MB
1. Theory Part 1 - RNNs and LSTMs/3. Introduction to RNNs Part 2.vtt
9.9 KB
1. Theory Part 1 - RNNs and LSTMs/4. Test Your Understanding.html
160 B
1. Theory Part 1 - RNNs and LSTMs/5. Playing with the Activations.mp4
71.6 MB
1. Theory Part 1 - RNNs and LSTMs/5. Playing with the Activations.vtt
10.9 KB
1. Theory Part 1 - RNNs and LSTMs/6. LSTMs.mp4
66.7 MB
1. Theory Part 1 - RNNs and LSTMs/6. LSTMs.vtt
10.7 KB
1. Theory Part 1 - RNNs and LSTMs/7. LSTM Variants.mp4
23.5 MB
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.mp4
22.8 MB
1. Theory Part 1 - RNNs and LSTMs/8. LSTM Step-by-Step Example Walktrough.vtt
4.6 KB
2. Theory Part 2 - Sequence Modeling/1. Sequence-to-Sequence Models.mp4
43.6 MB
2. Theory Part 2 - Sequence Modeling/1. Sequence-to-Sequence Models.vtt
10.3 KB
2. Theory Part 2 - Sequence Modeling/2. Attention Mechanisms.mp4
40.1 MB
2. Theory Part 2 - Sequence Modeling/2. Attention Mechanisms.vtt
7.1 KB
2. Theory Part 2 - Sequence Modeling/3. How Attention Mechanisms Work.mp4
36.8 MB
2. Theory Part 2 - Sequence Modeling/3. How Attention Mechanisms Work.vtt
8.1 KB
3. Practical Part 1 - Introduction to PyTorch/1. Installing PyTorch and an Introduction.mp4
72.9 MB
3. Practical Part 1 - Introduction to PyTorch/1. Installing PyTorch and an Introduction.vtt
12.6 KB
3. Practical Part 1 - Introduction to PyTorch/2. Torch Tensors Part 1.mp4
77.7 MB
3. Practical Part 1 - Introduction to PyTorch/2. Torch Tensors Part 1.vtt
13.2 KB
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/1. The Dataset.mp4
81.8 MB
4. Practical Part 2 - Processing the Dataset/1. The Dataset.vtt
11.2 KB
4. Practical Part 2 - Processing the Dataset/10. Getting Rid of Rare Words.mp4
82.5 MB
4. Practical Part 2 - Processing the Dataset/10. Getting Rid of Rare Words.vtt
10.3 KB
4. Practical Part 2 - Processing the Dataset/2. Processing the Dataset Part 1.mp4
68.1 MB
4. Practical Part 2 - Processing the Dataset/2. Processing the Dataset Part 1.vtt
7.6 KB
4. Practical Part 2 - Processing the Dataset/3. Processing the Data Part 2.mp4
73.8 MB
4. Practical Part 2 - Processing the Dataset/3. Processing the Data Part 2.vtt
9.3 KB
4. Practical Part 2 - Processing the Dataset/4. Processing the Dataset Part 3.mp4
75.7 MB
4. Practical Part 2 - Processing the Dataset/4. Processing the Dataset Part 3.vtt
10.2 KB
4. Practical Part 2 - Processing the Dataset/5. Processing the Dataset Part 4.mp4
56.2 MB
4. Practical Part 2 - Processing the Dataset/5. Processing the Dataset Part 4.vtt
7.5 KB
4. Practical Part 2 - Processing the Dataset/6. Processing the Words.mp4
89.2 MB
4. Practical Part 2 - Processing the Dataset/6. Processing the Words.vtt
13.6 KB
4. Practical Part 2 - Processing the Dataset/7. Processing the Text.mp4
95.6 MB
4. Practical Part 2 - Processing the Dataset/7. Processing the Text.vtt
10.9 KB
4. Practical Part 2 - Processing the Dataset/8. Processing the Text Part 2.mp4
95.6 MB
4. Practical Part 2 - Processing the Dataset/8. Processing the Text Part 2.vtt
10.1 KB
4. Practical Part 2 - Processing the Dataset/9. Filtering the Text.mp4
63.2 MB
4. Practical Part 2 - Processing the Dataset/9. Filtering the Text.vtt
7.8 KB
5. Practical Part 3 - Data Preperation/1. Preparing the Data for Model Part 1.mp4
87.1 MB
5. Practical Part 3 - Data Preperation/1. Preparing the Data for Model Part 1.vtt
14.2 KB
5. Practical Part 3 - Data Preperation/2. Understanding the zip function.mp4
45.4 MB
5. Practical Part 3 - Data Preperation/2. Understanding the zip function.vtt
6.4 KB
5. Practical Part 3 - Data Preperation/3. Preparing the Data for Model Part 2.mp4
55 MB
5. Practical Part 3 - Data Preperation/3. Preparing the Data for Model Part 2.vtt
9.3 KB
5. Practical Part 3 - Data Preperation/4. Preparing the Data for Model Part 3.mp4
88.6 MB
5. Practical Part 3 - Data Preperation/4. Preparing the Data for Model Part 3.vtt
12.2 KB
5. Practical Part 3 - Data Preperation/5. Preparing the Data for Model Part 4.mp4
104.3 MB
5. Practical Part 3 - Data Preperation/5. Preparing the Data for Model Part 4.vtt
15.2 KB
6. Practical Part 4 - Building the Model/1. Understanding the Encoder.mp4
53.2 MB
6. Practical Part 4 - Building the Model/1. Understanding the Encoder.vtt
6.8 KB
6. Practical Part 4 - Building the Model/2. Defining the Encoder.mp4
242.2 MB
6. Practical Part 4 - Building the Model/2. Defining the Encoder.vtt
28.1 KB
6. Practical Part 4 - Building the Model/3. Understanding Pack Padded Sequence.mp4
59.1 MB
6. Practical Part 4 - Building the Model/3. Understanding Pack Padded Sequence.vtt
8.4 KB
6. Practical Part 4 - Building the Model/4. Designing the Attention Model.mp4
151.5 MB
6. Practical Part 4 - Building the Model/4. Designing the Attention Model.vtt
18.3 KB
6. Practical Part 4 - Building the Model/5. Designing the Decoder Part 1.mp4
127.3 MB
6. Practical Part 4 - Building the Model/5. Designing the Decoder Part 1.vtt
16.7 KB
6. Practical Part 4 - Building the Model/6. Designing the Decoder Part 2.mp4
160.2 MB
6. Practical Part 4 - Building the Model/6. Designing the Decoder Part 2.vtt
20.4 KB
7. Practical Part 5 - Training the Model/1. Creating the Loss Function.mp4
67.5 MB
7. Practical Part 5 - Training the Model/1. Creating the Loss Function.vtt
7.4 KB
7. Practical Part 5 - Training the Model/2. Teacher Forcing.mp4
48.9 MB
7. Practical Part 5 - Training the Model/2. Teacher Forcing.vtt
7.3 KB
7. Practical Part 5 - Training the Model/3. Visualize Training Part 1.mp4
131.9 MB
7. Practical Part 5 - Training the Model/3. Visualize Training Part 1.vtt
16.4 KB
7. Practical Part 5 - Training the Model/4. Visualize Training Part 2.mp4
113.1 MB
7. Practical Part 5 - Training the Model/4. Visualize Training Part 2.vtt
12.7 KB
7. Practical Part 5 - Training the Model/5. Training.mp4
122.9 MB
7. Practical Part 5 - Training the Model/5. Training.vtt
14.4 KB
7. Practical Part 5 - Training the Model/6. Proceeding.html
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