LLM - Master Documents Splitting and Chunking

Character splitting, semantic chunking, recursive splitting, PDF processing, code handling, LangChain, Hugging Face, FAI

What you'll learn

• Master Text Splitting and Chunking techniques
• Master OpenAI, Langchain text splitters
• Text chunking using Open Source LLMs
• Implement code along exercises to build and optimize vector indexing systems for real-world applications

Requirements

• Basic Python programming knowledge
• Desire to learn and excel more
• Anyone who want to explore the world of AI and Vector Database

Description

How do you prepare data for AI success?

It all starts with mastering text chunking.

This course teaches essential techniques like character splitting, semantic chunking, and handling specialized documents like code and PDFs. Learn to use tools like LangChain and Hugging Face to optimize data for embeddings, similarity searches, and NLP workflows.

Unlock the secrets of effective document preprocessing for large language models with our comprehensive course, LLM - Master Document Splitting and Chunking. Designed for data professionals, AI enthusiasts, and developers, this course dives deep into the art and science of splitting and chunking text documents to maximize efficiency and accuracy in natural language processing tasks.

You will explore a variety of techniques and tools, from basic character splitting to advanced semantic chunking using LangChain and Hugging Face. Each section of the course is carefully structured to provide both theoretical knowledge and practical skills, equipping you with the ability to handle diverse document types, including markdown files, Python and JavaScript code, PDFs, and more.

You will learn the following with PRACTICAL HANDS-ON:

Introduction to Document Splitting and Chunking

• Understand the role of document splitting and chunking in NLP workflows.
• Explore essential resources for preparing data for large language models.
• Learn how effective text processing impacts model accuracy and efficiency.

Character-Based Splitting Techniques

• Discover how to split text documents at the character level for simpler workflows.
• Fine-tune chunk sizes and overlaps to optimize processing for various use cases.
• Access preview-enabled modules for hands-on experimentation with these techniques.

Recursive Text Splitting with LangChain

• Master recursive splitting techniques for structured and nested documents.
• Leverage LangChain's tools to handle complex text hierarchies with ease.
• Apply recursive splitting to enhance semantic understanding in NLP models.

Specialized Splitting for Document Types

• Learn advanced techniques to split markdown files, Python, and JavaScript code while preserving structural integrity.
• Extract text from PDFs, process it into embeddings with OpenAI and FAISS, and run effective similarity searches.
• Gain insights into tailoring text-splitting strategies for document-specific requirements.

Model-Driven Chunking Techniques

• Delve into semantic text splitting and its applications in modern NLP.
• Use LangChain and Hugging Face tools to perform intelligent text splitting.
• Understand embeddings and evaluate chunk relevance with cosine similarity comparisons.
• Preview-enabled sections allow you to try these techniques in real-world scenarios.

Semantic Chunking with LangChain

• Grasp the principles of semantic chunking and its impact on text understanding.
• Implement semantic chunking workflows using LangChain’s cutting-edge capabilities.
• Combine semantic chunking with embeddings to optimize downstream NLP tasks.

Why Take This Course?

• Learn industry-relevant skills in document preprocessing for machine learning
• Gain hands-on experience with popular tools like LangChain, Hugging Face, and OpenAI
• Understand how to optimize documents for embeddings and similarity searches
• Unlock new career opportunities in NLP and AI development

Join today to master document splitting and chunking techniques essential for modern AI workflows!

Who this course is for:

• Anyone who want to understand how to prepare data for LLM
• Anyone who wants to master techniques on how to best prepare the data for LLMs
• Anyone who wants to learn to apply OpenAI and Open Source LLMs for text splitting and chunking