practical project
DevEval: Evaluating Code Generation in Practical Software Projects
Li, Jia, Li, Ge, Zhao, Yunfei, Li, Yongmin, Jin, Zhi, Zhu, Hao, Liu, Huanyu, Liu, Kaibo, Wang, Lecheng, Fang, Zheng, Wang, Lanshen, Ding, Jiazheng, Zhang, Xuanming, Dong, Yihong, Zhu, Yuqi, Gu, Bin, Yang, Mengfei
How to evaluate Large Language Models (LLMs) in code generation is an open question. Many benchmarks have been proposed but are inconsistent with practical software projects, e.g., unreal program distributions, insufficient dependencies, and small-scale project contexts. Thus, the capabilities of LLMs in practical projects are still unclear. In this paper, we propose a new benchmark named DevEval, aligned with Developers' experiences in practical projects. DevEval is collected through a rigorous pipeline, containing 2,690 samples from 119 practical projects and covering 10 domains. Compared to previous benchmarks, DevEval aligns to practical projects in multiple dimensions, e.g., real program distributions, sufficient dependencies, and enough-scale project contexts. We assess five popular LLMs on DevEval (e.g., gpt-4, gpt-3.5-turbo, CodeLLaMa, and StarCoder) and reveal their actual abilities in code generation. For instance, the highest Pass@1 of gpt-3.5-turbo only is 42 in our experiments. We also discuss the challenges and future directions of code generation in practical projects. We open-source DevEval and hope it can facilitate the development of code generation in practical projects.
Modern AI Masterclass: Build 6 Real World AI Applications
Modern AI Masterclass: Build 6 Real World AI Applications, Harness the power of AI to solve practical, real-world problems in Finance, Tech, Art and Healthcare Created by Dr. Ryan Ahmed, Ph.D., MBA, Kirill Eremenko, Hadelin de Ponteves, SuperDataScience Team,Mitchell Bouchard PREVIEW THIS COURSE - GET COUPON CODE Description Artificial Intelligence (AI) revolution is here! "Artificial Intelligence market worldwide is projected to grow by US$284.6 Billion driven by a compounded growth of 43. Deep Learning, one of the segments analyzed and sized in this study, displays the potential to grow at over 42. AI is the science that empowers computers to mimic human intelligence such as decision making, reasoning, text processing, and visual perception. AI is a broader general field that entails several sub-fields such as machine learning, robotics, and computer vision.
Python & Machine Learning for Financial Analysis
Created by Dr. Ryan Ahmed, Ph.D., MBA Are you ready to learn python programming fundamentals and directly apply them to solve real world applications in Finance and Banking? If the answer is yes, then welcome to the "The Complete Python and Machine Learning for Financial Analysis" course in which you will learn everything you need to develop practical real-world finance/banking applications in Python! Python is ranked as the number one programming language to learn in 2020, here are 6 reasons you need to learn Python right now! The course is divided into 3 main parts covering python programming fundamentals, financial analysis in Python and AI/ML application in Finance/Banking Industry. In addition, this section will cover key Python libraries for data science such as Numpy and Pandas.
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Are you ready to learn python programming fundamentals and directly apply them to solve real world applications in Finance and Banking? If the answer is yes, then welcome to the "The Complete Python and Machine Learning for Financial Analysis" course in which you will learn everything you need to develop practical real-world finance/banking applications in Python! Python is ranked as the number one programming language to learn in 2020, here are 6 reasons you need to learn Python right now! The course is divided into 3 main parts covering python programming fundamentals, financial analysis in Python and AI/ML application in Finance/Banking Industry. In addition, this section will cover key Python libraries for data science such as Numpy and Pandas.
Learning AI if You Suck at Math -- Part Two -- Practical Projects
If you read the first article in this series, you're already on your way to upping your math game. Maybe some of those funny little symbols are starting to make sense. Also be sure to check out parts 3, 4, 5, 6 and 7. But here's another dirty little secret nobody tells you about AI: If you're a developer or sys-admin you probably already use a lot of libraries and frameworks that you know little about. You don't have to understand the inner workings of web-scraping to use curl.