“Birds of a feather flock together” is a common phenomenon in real life, indicating that similar things are likely to have similar attributes. Using this idea, machine learning can classify data, assigning it to the same category, such as similar or “nearest” neighbors. Today, let’s learn about nearest neighbor classification. 1. Understanding Nearest Neighbor Classification … Read more
Research Background In the era of big data and artificial intelligence, the position of literature as a core knowledge carrier has not changed. However, the current methods of literature resource management, such as information retrieval, databases, subject headings, and classification systems, cannot meet the higher-level needs of researchers. The knowledge graph is a novel mass … Read more
1. From Confusion to Curiosity: First Impressions of LangGraph In this era deeply permeated by large model technology, while we enjoy the many conveniences it brings, we are also faced with a series of thorny issues. Take my daily work with large models, for instance; they indeed perform excellently in handling simple tasks, such as … Read more
Notes from Andrew Ng’s DeepLearning.ai Course 【Andrew Ng’s DeepLearning.ai Notes 1】Intuitive Explanation of Logistic Regression 【Andrew Ng’s DeepLearning.ai Notes 2】Simple Explanation of Neural Networks (Part 1) 【Andrew Ng’s DeepLearning.ai Notes 2】Simple Explanation of Neural Networks (Part 2) Having trouble with deep networks? Andrew Ng helps you optimize neural networks (1) 【DeepLearning.ai】Deep Learning: Optimizing Neural Networks … Read more
After a year of development, domestic AI has gradually matured. Today, let’s look at how people can combine the domestic star product Zhipu AI with the LlamaIndex data framework to handle daily tasks. Domestic AI Products As we all know, the AI and large model field has been extremely hot this past year. In August, … Read more
The full name of RAG is Retrieval Augmented Generation, which means “retrieval enhanced generation”. LLMs are trained on a vast amount of data, but this training data does not include your data. RAG solves this problem by adding your data to the data that the LLM already has access to. In RAG, your data is … Read more
Click the “Blue Words” to Follow Us LlamaIndex, as a powerful framework, provides a solid foundation for building data pipelines that connect with large language models (LLMs). It implements a modular approach to query execution through structured workflows, simplifying solutions to complex problems. Today, let’s discuss the workflows of LlamaIndex. 1. Basics of LlamaIndex Workflows … Read more
Today, let’s continue to introduce a “wheel”. In this era of information explosion, data is no longer a scarce resource; it is everywhere, like air. However, data itself does not equal wisdom. We are like boats floating in an ocean, surrounded by endless waters, and only by mastering the compass that guides our direction can … Read more
Introduction This sharing is titled “RAG 2.0 Engine Design Challenges and Implementation”. Main content includes the following parts: 1. Pain points and solutions of RAG 1.0 2. How to effectively Chunking 3. How to accurately recall 4. Advanced RAG and preprocessing 5. How RAG will develop in the future 6. Q&A Guest Speaker｜Zhang Yingfeng Founder … Read more
In the workplace, efficiency is the goal pursued by every professional. However, tasks such as creating PPTs, organizing data, and searching for information often become headaches for employees. When facing looming deadlines, do you feel overwhelmed yet still unable to keep up? Now, with the gradual maturity of AI technology, many workplace pain points are … Read more