This intensive 8-hour tutorial will provide a hands-on introduction to two of the most important techniques for getting the most out of large language models: prompt engineering and retrieval augmented generation (RAG). In the first half of the course, you will learn prompt engineering techniques like zero-shot prompting, few-shot prompting, chain-of-thought prompting, and more to […]
Title: Data-Driven Turbulence Modeling and Simulation Abstract Turbulent fluid flows are characterized by a wide spectrum of spatial and temporal scales.Unfortunately, the cost of resolving these scales with Direct Numerical Simulation (DNS) growsquickly with Reynolds number, so engineers will be unable to apply DNS to aerodynamic flows ofindustrial interest for many decades to come. Alternatively, […]
TrAC DLRG Mini-course on Fundamentals of Deep Learning (class 1/3) In this mini-course, we will cover basic fundamental concepts of deep learning. This is a series of 3 lectures spread over 3 weeks.
TrAC ADLRG Mini-course on Deep Reinforcement Learning (class 1/3) In this mini-course, we will cover concepts in deep reinforcement learning. To register for this course, visit this link: https://trac-ai.iastate.edu/2024/01/16/trac-events-for-spring-2024/news/
TrAC DLRG Mini-course on Fundamentals of Deep Learning (class 2/3) In this mini-course, we will cover basic fundamental concepts of deep learning. This is a series of 3 lectures spread […]
Title: HARVEST: High-Performance Artificial Vision Framework for Expert Labeling using Semi-Supervised Training Abstract Three valuable crop scouting use cases are to provide i) recommendations of optimum rate and timing of nitrogen, ii) identifying plant disease incidence & severity followed by recommending treatment options, and iii) predicting yield to inform a farmer’s grain marketing activities. While […]
TrAC ADLRG Mini-course on Deep Reinforcement Learning (class 2/3) In this mini-course, we will cover concepts in deep reinforcement learning.
Introduction Optimization has been playing a critical role in modern machine learning, leading to its significantly successful applications in many different fields. Researchers and practitioners typically spend less time investigating optimizers when they do the model training, mostly following some empirical rules or recommendations from the community. In this event, we will go relatively deeper […]
TrAC DLRG Mini-course on Fundamentals of Deep Learning (class 3/3) In this mini-course, we will cover basic fundamental concepts of deep learning. This is a series of 3 lectures spread over 3 weeks.
Title: The “Fatal Flaw” in AI Policy & Governance, and a Simple Yet Strategic Framework that May Help Abstract Much of policy and governance for AI can be divided into three broad categories. There are “soft law” mechanisms, such as ethics frameworks and guidelines. There are calls for and efforts toward creating new regulations or […]
TrAC ADLRG Mini-course on Deep Reinforcement Learning (class 3/4) In this mini-course, we will cover concepts in deep reinforcement learning.
TrAC DLRG Mini-course on Mastering PyTorch (class 1/3) In this mini-course, we will cover programming for deep learning and accelerated computing using PyTorch. This is a series of 3 lectures spread over 3 weeks.
