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  • React
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NEW

Building AI Applications with RAG and Tool Use

If you want to learn RAG fast, these five platforms balance ready-made data connectors, decent docs, and reasonable setup effort. *Time estimates assume a small team (2‑3 engineers) following a typical bootcamp curriculum and include basic testing. Group RAG builds into three buckets and ask how…
Thumbnail Image of Tutorial Building AI Applications with RAG and Tool Use
Image of Author Dr. Dipen
Dr. Dipen
I am an AI/ML researcher with 150+ citations and 16 published research papers. I have three tier-1 publications, including Internet of Things (Elsevier), Biomedical Signal Processing and Control (Elsevier), and IEEE Access. In my research journey, I have collaborated with NASA Glenn Research Center, Cleveland Clinic, and the U.S. Department of Energy for various research projects. I am also an official reviewer and have reviewed over 100 research papers for Elsevier, IEEE Transactions, ICRA, MDPI, and other top journals and conferences. I hold a PhD from Cleveland State University with a focus on large language models (LLMs) in cybersecurity, and I also earned a master’s degree in informatics from Northeastern University.
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What Is AWQ in LLM Quantization and How It Works

AWQ stands for activation-aware weight quantization. It scales the most influential weight channels based on offline activation statistics, then quantizes everything else to ultra-low bit widths. By protecting a small fraction of salient weights, it keeps quantization error down without…
Thumbnail Image of Tutorial What Is AWQ in LLM Quantization and How It Works
Image of Author Dr. Dipen
Dr. Dipen
I am an AI/ML researcher with 150+ citations and 16 published research papers. I have three tier-1 publications, including Internet of Things (Elsevier), Biomedical Signal Processing and Control (Elsevier), and IEEE Access. In my research journey, I have collaborated with NASA Glenn Research Center, Cleveland Clinic, and the U.S. Department of Energy for various research projects. I am also an official reviewer and have reviewed over 100 research papers for Elsevier, IEEE Transactions, ICRA, MDPI, and other top journals and conferences. I hold a PhD from Cleveland State University with a focus on large language models (LLMs) in cybersecurity, and I also earned a master’s degree in informatics from Northeastern University.
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NEW

Prompt Engineering Techniques for Better LLM Results

*Time estimates are approximate and reflect typical pacing for learners working through the course material. The simple techniques, like zero-shot and role prompting, take minutes to learn. The advanced ones, like self-consistency and RAG, take hours. They also assume you already understand how the…
Thumbnail Image of Tutorial Prompt Engineering Techniques for Better LLM Results
Image of Author Dr. Dipen
Dr. Dipen
I am an AI/ML researcher with 150+ citations and 16 published research papers. I have three tier-1 publications, including Internet of Things (Elsevier), Biomedical Signal Processing and Control (Elsevier), and IEEE Access. In my research journey, I have collaborated with NASA Glenn Research Center, Cleveland Clinic, and the U.S. Department of Energy for various research projects. I am also an official reviewer and have reviewed over 100 research papers for Elsevier, IEEE Transactions, ICRA, MDPI, and other top journals and conferences. I hold a PhD from Cleveland State University with a focus on large language models (LLMs) in cybersecurity, and I also earned a master’s degree in informatics from Northeastern University.
•Last Updated:
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NEW

PNPM Tutorial for Monorepos and AI App Projects

A pnpm setup aimed at AI monorepos can roughly halve setup time and keep model artifacts versioned without the usual mess. The numbers below cover the three things you'll actually measure: install speed, disk footprint, and CI latency. That's enough to decide whether pnpm earns a spot in your…
Thumbnail Image of Tutorial PNPM Tutorial for Monorepos and AI App Projects
Image of Author Dr. Dipen
Dr. Dipen
I am an AI/ML researcher with 150+ citations and 16 published research papers. I have three tier-1 publications, including Internet of Things (Elsevier), Biomedical Signal Processing and Control (Elsevier), and IEEE Access. In my research journey, I have collaborated with NASA Glenn Research Center, Cleveland Clinic, and the U.S. Department of Energy for various research projects. I am also an official reviewer and have reviewed over 100 research papers for Elsevier, IEEE Transactions, ICRA, MDPI, and other top journals and conferences. I hold a PhD from Cleveland State University with a focus on large language models (LLMs) in cybersecurity, and I also earned a master’s degree in informatics from Northeastern University.
•Last Updated:
00
Read Full Article
NEW

What Is AWQ in LLM Quantization and How to Use It

AWQ is a post-training quantization technique that packs large language models into 4-bit weight formats while shielding the ~1% of salient weights that actually drive quality. In practice it cuts VRAM roughly in half and buys 1.5–3× faster inference than FP16, which is exactly the kind of resource…
Thumbnail Image of Tutorial What Is AWQ in LLM Quantization and How to Use It
Image of Author Dr. Dipen
Dr. Dipen
I am an AI/ML researcher with 150+ citations and 16 published research papers. I have three tier-1 publications, including Internet of Things (Elsevier), Biomedical Signal Processing and Control (Elsevier), and IEEE Access. In my research journey, I have collaborated with NASA Glenn Research Center, Cleveland Clinic, and the U.S. Department of Energy for various research projects. I am also an official reviewer and have reviewed over 100 research papers for Elsevier, IEEE Transactions, ICRA, MDPI, and other top journals and conferences. I hold a PhD from Cleveland State University with a focus on large language models (LLMs) in cybersecurity, and I also earned a master’s degree in informatics from Northeastern University.
•Last Updated:
00
Read Full Article

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