Building Your Own Large Language Model
Et Tu Code
Building Your Own Large Language Model: A Step-by-Step Guide is your comprehensive roadmap to crafting custom language models tailored to diverse applications.
From laying the groundwork in Language Model Development Fundamentals to navigating through Essential NLP Concepts and Framework Selection, each step is meticulously detailed to ensure mastery. You'll learn the art of Data Collection and Preprocessing, crucial for gathering and refining training data, followed by the craft of Scalable Model Architecture Design. Training and Fine-Tuning Strategies guide you through efficiently honing your model's capabilities, while Performance Evaluation and Validation ensure accuracy. Model Deployment integrates your creation seamlessly into real-world applications like chatbots or language translation tools, while Task-Specific Fine-Tuning customizes it for sentiment analysis or text summarization. Ethical Considerations address biases and ethical concerns, while Performance Optimization techniques enhance efficiency. Through Exploration of Large Language Models, you'll grasp the landscape's nuances, preparing for Application Integration and Scaling with Distributed Training. Continuous Improvement methodologies, coupled with a focus on Interpretability and a glimpse into Future Trends, equip you for ongoing success. Real-world Case Studies provide practical insights, and Community Engagement fosters collaboration.
Concluding with key takeaways and recommendations, this guide propels you into the dynamic realm of large language model development with confidence and clarity. 🚀
Duration - 5h 46m.
Author - Et Tu Code.
Narrator - Helen Green.
Published Date - Saturday, 20 January 2024.
Copyright - © 2023 Et Tu Code ©.
Location:
United States
Description:
Building Your Own Large Language Model: A Step-by-Step Guide is your comprehensive roadmap to crafting custom language models tailored to diverse applications. From laying the groundwork in Language Model Development Fundamentals to navigating through Essential NLP Concepts and Framework Selection, each step is meticulously detailed to ensure mastery. You'll learn the art of Data Collection and Preprocessing, crucial for gathering and refining training data, followed by the craft of Scalable Model Architecture Design. Training and Fine-Tuning Strategies guide you through efficiently honing your model's capabilities, while Performance Evaluation and Validation ensure accuracy. Model Deployment integrates your creation seamlessly into real-world applications like chatbots or language translation tools, while Task-Specific Fine-Tuning customizes it for sentiment analysis or text summarization. Ethical Considerations address biases and ethical concerns, while Performance Optimization techniques enhance efficiency. Through Exploration of Large Language Models, you'll grasp the landscape's nuances, preparing for Application Integration and Scaling with Distributed Training. Continuous Improvement methodologies, coupled with a focus on Interpretability and a glimpse into Future Trends, equip you for ongoing success. Real-world Case Studies provide practical insights, and Community Engagement fosters collaboration. Concluding with key takeaways and recommendations, this guide propels you into the dynamic realm of large language model development with confidence and clarity. 🚀 Duration - 5h 46m. Author - Et Tu Code. Narrator - Helen Green. Published Date - Saturday, 20 January 2024. Copyright - © 2023 Et Tu Code ©.
Language:
English
Opening Credits
Duration:02:13:28
2 preface
Duration:02:43:16
3 Introduction to language model development
Duration:05:48:16
4 Basics of natural language processing
Duration:03:20:48
5 Choosing the right framework
Duration:04:57:12
6 collecting and preprocessing data
Duration:04:43:16
7 model architecture design
Duration:05:26:04
8 training and fine tuning
Duration:05:52:28
9 evaluation metrics and validation
Duration:05:33:02
10 deploying your language model
Duration:04:35:00
11 fine tuning for specific use cases
Duration:06:44:55
12 handling ethical and bias considerations
Duration:04:27:09
13 optimizing performance and efficiency
Duration:04:50:55
14 popular large language models
Duration:06:06:38
15 popular large language models gpt 3 (generative pre trained transformer 3)
Duration:04:36:57
16 popular large language models bert (bidirectional encoder representations from transformers)
Duration:03:59:31
17 popular large language models t5 (text to text transfer transformer)
Duration:05:49:12
18 popular large language models xlnet
Duration:03:59:50
19 popular large language models roberta (robustly optimized bert approach)
Duration:05:15:31
20 popular large language models llama 2
Duration:04:21:00
21 popular large language models google's gemini
Duration:06:04:21
22 integrating language model with applications
Duration:04:38:02
23 scaling and distributed training
Duration:04:15:38
24 continuous improvement and maintenance
Duration:03:15:36
25 interpretable ai and explainability
Duration:06:20:24
26 challenges and future trends
Duration:04:24:21
27 case studies and project examples
Duration:04:50:57
28 community and collaboration
Duration:04:57:07
29 conclusion
Duration:04:47:33
30 glossary
Duration:04:36:31
31 bibliography
Duration:05:00:12
Ending Credits
Duration:01:14:38