PyTorch for Natural Language Processing Mastery : Build powerful dialogue models with Python
PYTORCH for Natural Language Processing Mastery: Build Powerful Dialogue Models with Python About the Technology Dialo
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English Pages 105 Year 2024
Table of contents :
CHAPTER 1: INTRODUCTION TO DIALOGUE SYSTEMS AND NLP
1.2 Unlocking Human-Computer Interaction: The Magic of Natural Language Processing (NLP)
CHAPTER 2: DEMYSTIFYING PYTORCH
2.1 Getting Started with PyTorch
2.2 Mastering the Fundamentals: Unveiling the Power of Core PyTorch Functionalities
2.3 Equipping Your Toolkit: Expanding Your NLP Arsenal with Specialized Libraries
CHAPTER 3: DIALOGUE MODELING: THE CORE CONCEPTS
3.2 Approaches to Building Dialogue Systems: A Journey Through Methodologies
3.3 Evaluating Success: Measuring the Quality of Conversations
CHAPTER 4: CRAFTING A SIMPLE RULE-BASED DIALOGUE SYSTEM
4.2 Beyond the Simple: Exploring the Frontiers of Dialogue Systems
CHAPTER 5: SEQUENCE-TO-SEQUENCE MODELS: POWERING DIALOGUE GENERATION
5.1 Understanding Seq2seq: The Backbone of Conversational AI
5.2 Encoder-Decoder Architecture: Unveiling the Core Components
5.3 Building a Simple Seq2seq Model for Dialogue Generation (PyTorch Example)
CHAPTER 6: ADVANCING TO TRANSFORMERS: THE CUTTING EDGE
6.2 Transformer-based Encoder-Decoder Architectures:
6.3 Fine-tuning Pre-trained Transformers: Building Powerful Dialogue Models in PyTorch
CHAPTER 7: DIALOGUE STATE TRACKING: KEEPING THE CONTEXT FLOWING
7.2 Long Short-Term Memory Networks: Remembering the Conversation Flow
7.3 LSTMs with Attention: Supercharging Dialogue State Tracking in PyTorch
CHAPTER 8: FINE-TUNING PRE-TRAINED MODELS
8.2 Fine-tuning Techniques: Unlocking the Potential of Pre-trained Models
8.3 Real-World Application: Fine-tuning for Dialogue Generation and Intent Classification in PyTorch
CHAPTER 9: OPEN-DOMAIN DIALOGUE SYSTEMS: THE NEXT FRONTIER
9.2 Expanding the Toolkit: Empowering Open-Domain Dialogue Systems
CHAPTER 10: EVALUATION AND DEPLOYMENT: PUTTING YOUR MODELS TO THE TASK
10.1 Evaluating Performance: Measuring Success Beyond Just Accuracy
10.2 Real-World Deployment: Bringing Your Dialogue System to Life
CHAPTER 11: ETHICAL CONSIDERATIONS AND FUTURE TRENDS: LOOKING FORWARD
11.2 Emerging Trends and Advancements: Glimpsing the Future of Dialogue Systems
CHAPTER 1: INTRODUCTION TO DIALOGUE SYSTEMS AND NLP
1.2 Unlocking Human-Computer Interaction: The Magic of Natural Language Processing (NLP)
CHAPTER 2: DEMYSTIFYING PYTORCH
2.1 Getting Started with PyTorch
2.2 Mastering the Fundamentals: Unveiling the Power of Core PyTorch Functionalities
2.3 Equipping Your Toolkit: Expanding Your NLP Arsenal with Specialized Libraries
CHAPTER 3: DIALOGUE MODELING: THE CORE CONCEPTS
3.2 Approaches to Building Dialogue Systems: A Journey Through Methodologies
3.3 Evaluating Success: Measuring the Quality of Conversations
CHAPTER 4: CRAFTING A SIMPLE RULE-BASED DIALOGUE SYSTEM
4.2 Beyond the Simple: Exploring the Frontiers of Dialogue Systems
CHAPTER 5: SEQUENCE-TO-SEQUENCE MODELS: POWERING DIALOGUE GENERATION
5.1 Understanding Seq2seq: The Backbone of Conversational AI
5.2 Encoder-Decoder Architecture: Unveiling the Core Components
5.3 Building a Simple Seq2seq Model for Dialogue Generation (PyTorch Example)
CHAPTER 6: ADVANCING TO TRANSFORMERS: THE CUTTING EDGE
6.2 Transformer-based Encoder-Decoder Architectures:
6.3 Fine-tuning Pre-trained Transformers: Building Powerful Dialogue Models in PyTorch
CHAPTER 7: DIALOGUE STATE TRACKING: KEEPING THE CONTEXT FLOWING
7.2 Long Short-Term Memory Networks: Remembering the Conversation Flow
7.3 LSTMs with Attention: Supercharging Dialogue State Tracking in PyTorch
CHAPTER 8: FINE-TUNING PRE-TRAINED MODELS
8.2 Fine-tuning Techniques: Unlocking the Potential of Pre-trained Models
8.3 Real-World Application: Fine-tuning for Dialogue Generation and Intent Classification in PyTorch
CHAPTER 9: OPEN-DOMAIN DIALOGUE SYSTEMS: THE NEXT FRONTIER
9.2 Expanding the Toolkit: Empowering Open-Domain Dialogue Systems
CHAPTER 10: EVALUATION AND DEPLOYMENT: PUTTING YOUR MODELS TO THE TASK
10.1 Evaluating Performance: Measuring Success Beyond Just Accuracy
10.2 Real-World Deployment: Bringing Your Dialogue System to Life
CHAPTER 11: ETHICAL CONSIDERATIONS AND FUTURE TRENDS: LOOKING FORWARD
11.2 Emerging Trends and Advancements: Glimpsing the Future of Dialogue Systems
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