AI won’t replace programmers, but rather make it easier for programmers to replace everyone else.
CODE
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AI Engineer Bot: Build RAG Chats, Agents, and ML Models
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AI Building AI Tell the bot, or in this case, our AI engineer, what to build, and it can: •Create a RAG chat
•Build an AI agent
•Operate on your code base and generate PRs
•Build structured data ML models -
Eight Dimensions of Data Quality for AI Machine Learning
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Understanding the eight dimensions of data quality https://
bit.ly/4gIQFaC
#AI #MachineLearning #DeepLearning #LLMs #DataScience -
Simple Framework for AI Agents by Abacus AI
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Check out this simple framework for #AI Agents from @AbacusAI at https://
abacus.ai/ai_agents • Connect to any data source or vector store
• Uses code execution engine
• Orchestrate with other ML models
• LLM-agnostic for flexibility
• Designed for chat or task-based operations -
LoRA Tutorial and Additional Tips from Readers
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Glad you found it useful, and thanks for the kind words! I think you probably already read that, but there is a LoRA from-scratch tutorial in the last Appendix. There was a reader how also had some useful additional tips regarding LoRA:
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SAS Viya Workbench: Essential Programming Tool for Developers
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Find out why SAS Viya Workbench is @cjdinger
's new favorite tool for SAS programming work. -
RAG Search Approaches: Keyword vs Embedding Methods
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Here’s a quick rundown of the most popular (RAG) search approaches out there, plus tips on when they shine: • Keyword Search (e.g., BM25, BM42): Finds direct matches—great for straightforward data or well-defined keywords. • Embedding Search: Captures deeper semantics,
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LLM Fine-Tuning Notebooks with OpenAI and Hugging Face
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check out some of my latest notebooks containing llm fine-tuning using OAI and HF fine-tuners https://
github.com/avikumart/LLM-
GenAI-Transformers-Notebooks/tree/main/TMLC_LLM_projects
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LangChain maintains high issue ratio despite large star count
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fun fact, langchain has a super high ratio as well, despite a very high star count
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LangGraph: Production-Ready Agent Framework Low Level Control
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Because langgraph is a production ready agent framework… it’s very low level, highly controllable, no hidden prompts Helps you get to production without getting in the way, so high usage But a bit of a steeper learning curve (we’re working on that!) so less GitHub stars