The Complete LLM Engineer's Handbook: From Conceptualization to Production of Large Language Models
Sammy Oneal
This audiobook is narrated by a digital voice.
The world of Large Language Models (LLMs) is rapidly evolving, transforming industries and redefining the boundaries of artificial intelligence. "The Complete LLM Engineer's Handbook: From Conceptualization to Production of Large Language Models" is your comprehensive guide to understanding and mastering this cutting-edge technology. This book offers a thorough exploration of LLMs, from their foundational concepts to their practical applications in real-world scenarios. Whether you are a seasoned engineer, a curious researcher, or a tech enthusiast, this handbook is designed to equip you with the knowledge and skills needed to navigate the complexities of LLMs. This book delves into the intricate process of developing and deploying LLMs, providing a step-by-step approach that covers everything from the initial conceptualization to the final production stages. Readers will gain insights into the theoretical underpinnings of LLMs, including the latest advancements in natural language processing and machine learning. Practical examples and case studies are interspersed throughout the text, illustrating how these models can be fine-tuned and optimized for various applications, such as chatbots, content generation, and data analysis.
Duration - 6h 3m.
Author - Sammy Oneal.
Narrator - Digital Voice Ava G.
Published Date - Sunday, 26 January 2025.
Copyright - © 2025 Shandi Gallo ©.
Location:
United States
Description:
This audiobook is narrated by a digital voice. The world of Large Language Models (LLMs) is rapidly evolving, transforming industries and redefining the boundaries of artificial intelligence. "The Complete LLM Engineer's Handbook: From Conceptualization to Production of Large Language Models" is your comprehensive guide to understanding and mastering this cutting-edge technology. This book offers a thorough exploration of LLMs, from their foundational concepts to their practical applications in real-world scenarios. Whether you are a seasoned engineer, a curious researcher, or a tech enthusiast, this handbook is designed to equip you with the knowledge and skills needed to navigate the complexities of LLMs. This book delves into the intricate process of developing and deploying LLMs, providing a step-by-step approach that covers everything from the initial conceptualization to the final production stages. Readers will gain insights into the theoretical underpinnings of LLMs, including the latest advancements in natural language processing and machine learning. Practical examples and case studies are interspersed throughout the text, illustrating how these models can be fine-tuned and optimized for various applications, such as chatbots, content generation, and data analysis. Duration - 6h 3m. Author - Sammy Oneal. Narrator - Digital Voice Ava G. Published Date - Sunday, 26 January 2025. Copyright - © 2025 Shandi Gallo ©.
Language:
English
Chapter 1: Introduction to Large Language Models 4
Duration:00:00:05
1.1 Definition and Importance of Large Language Models (LLMs) 4
Duration:00:07:41
1.2 Brief History and Evolution of LLMs 9
Duration:00:07:59
1.3 Key Applications of LLMs in Industry 15
Duration:00:17:38
Chapter 2: Understanding the Basics of LLMs 28
Duration:00:00:05
2.1 Core Concepts and Terminology 28
Duration:00:07:13
2.2 How LLMs Differ from Traditional NLP Models 33
Duration:00:09:28
2.3 The Role of Deep Learning in LLMs 39
Duration:00:07:41
Chapter 3: Architectures of Large Language Models 46
Duration:00:00:05
3.1 Overview of Common Architectures 46
Duration:00:08:21
3.2 Transformers and Self-Attention Mechanism 52
Duration:00:09:09
3.3 Variants of Transformer Models 58
Duration:00:09:17
Chapter 4: Data Preparation for LLMs 65
Duration:00:00:05
4.1 Data Collection Strategies 65
Duration:00:08:01
4.2 Data Cleaning and Preprocessing Techniques 70
Duration:00:06:52
4.3 Handling Large-Scale Datasets 75
Duration:00:06:40
Chapter 5: Training Large Language Models 81
Duration:00:00:04
5.1 Overview of Training Processes 81
Duration:00:06:17
5.2 Hyperparameter Tuning and Optimization 86
Duration:00:08:13
5.3 Hardware and Infrastructure Requirements 91
Duration:00:09:15
Chapter 6: Fine-Tuning and Transfer Learning 99
Duration:00:00:04
6.1 Fine-Tuning Pre-trained Models 99
Duration:00:07:31
6.2 Transfer Learning Techniques 104
Duration:00:06:54
6.3 Case Studies of Successful Fine-Tuning 109
Duration:00:08:36
Chapter 7: Evaluating Large Language Models 116
Duration:00:00:05
7.1 Metrics for Evaluating LLMs 116
Duration:00:07:47
7.2 Common Evaluation Methods 121
Duration:00:09:13
7.3 Interpreting Evaluation Results 128
Duration:00:08:10
Chapter 8: Ethical Considerations and Bias Mitigation 134
Duration:00:00:06
8.1 Understanding Ethical Issues in LLMs 134
Duration:00:06:25
8.2 Identifying and Mitigating Bias 139
Duration:00:06:27
8.3 Ensuring Responsible AI Development 143
Duration:00:07:21
Chapter 9: Deploying Large Language Models 149
Duration:00:00:04
9.1 Deployment Strategies and Best Practices 149
Duration:00:06:26
9.2 Scaling LLMs for Production 154
Duration:00:08:11
9.3 Monitoring and Maintenance 159
Duration:00:07:41
Chapter 10: Advanced Topics in LLMs 165
Duration:00:00:04
10.1 Multi-Modal Models 165
Duration:00:05:23
10.2 Few-Shot and Zero-Shot Learning 169
Duration:00:06:06
10.3 Research Frontiers in LLMs 173
Duration:00:07:23
Chapter 11: Case Studies and Real-World Applications 179
Duration:00:00:05
11.1 Industry Use Cases 179
Duration:00:12:54
11.2 Success Stories and Lessons Learned 187
Duration:00:07:27
11.3 Future Trends and Predictions 193
Duration:00:08:39
Chapter 12: Tools and Frameworks for LLM Development 199
Duration:00:00:05
12.1 Popular Libraries and Frameworks 199
Duration:00:08:44
12.2 Development Tools and Platforms 205
Duration:00:07:58
12.3 Integrating LLMs with Existing Systems 210
Duration:00:08:44
Chapter 13: Security and Privacy in LLMs 217
Duration:00:00:05
13.1 Security Challenges in LLM Development 217
Duration:00:07:26
13.2 Privacy Concerns and Mitigation Strategies 222
Duration:00:06:59
13.3 Regulatory Compliance 227
Duration:00:07:11
Chapter 14: Community and Ecosystem 232
Duration:00:00:05
14.1 Open Source Contributions 232
Duration:00:06:16
14.2 Collaborative Projects and Research 236
Duration:00:07:59
14.3 Building a Career in LLM Engineering 242
Duration:00:06:12
Chapter 15: Future Directions and Innovations 247
Duration:00:00:05
15.1 Emerging Trends in LLM Research 247
Duration:00:10:36
15.2 Potential Breakthroughs and Innovations 254
Duration:00:08:58
15.3 The Road Ahead for LLMs 260
Duration:00:06:37