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所在平台: Udemy |
课程主页: https://www.udemy.com/course/autonomous-cars-deep-learning-and-computer-vision-in-python/
课程评论：没有评论
课程名称：自主驾驶汽车：在Python中的深度学习和计算机视觉 概述： 自主驾驶汽车正在引领汽车行业的范式转变，从传统的人驾车转向智能、自主驱动的人工智能车辆。自驾车提供了一种安全、高效且具成本效益的解决方案，预计将彻底改变人类出行的未来。到2035年，自驾车预计将拯救超过50万人生命，并产生超过1万亿美元的经济机会。随着世界向无驾驶的未来迈进，对这一新兴领域的经验丰富工程师和研究人员的需求从未如此迫切。 本课程旨在向学生提供自主驾驶车辆设计和开发的关键知识，使学生获得有关自驾车的各种概念的实践经验，如机器学习和计算机视觉。课程将介绍车道检测、交通标志分类、车辆/物体检测、人工智能和深度学习等概念。课程面向希望深入理解自主驾驶车辆控制的学生，建议具有基本编程知识，但课程初期将广泛涵盖相关内容，因此不设先决条件，欢迎任何有基本编程知识的学生参加。选修此课程的学生将掌握将重塑交通未来的无人驾驶汽车技术。 本课程将涉及的工具和算法包括： - OpenCV - 深度学习和人工神经网络 - 卷积神经网络 - 模板匹配 - HOG特征提取 - SIFT、SURF、FAST和ORB - Tensorflow和Keras - 线性回归和逻辑回归 - 决策树 - 支持向量机 - 朴素贝叶斯 讲师包括： - Dr. Ryan Ahmed，拥有专注于电动车控制系统的工程博士学位； - Frank Kane，曾在亚马逊专注于机器学习9年。 两位讲师在Udemy上共教授了超过50万名学生。曾学习过“Python数据科学、深度学习和机器学习”课程的学生可能会发现其中一些主题与该课程有重复，然而大部分内容聚焦于自主驾驶汽车所特有的计算机视觉技术，此处有许多新的、有价值的技能等待学习！
Autonomous Cars: Computer Vision and Deep Learning The automotive industry is experiencing a paradigm shift from conventional, human-driven vehicles into self-driving, artificial intelligence-powered vehicles. Self-driving vehicles offer a safe, efficient, and cost effective solution that will dramatically redefine the future of human mobility. Self-driving cars are expected to save over half a million lives and generate enormous economic opportunities in excess of $1 trillion dollars by 2035. The automotive industry is on a billion-dollar quest to deploy the most technologically advanced vehicles on the road. As the world advances towards a driverless future, the need for experienced engineers and researchers in this emerging new field has never been more crucial.The purpose of this course is to provide students with knowledge of key aspects of design and development of self-driving vehicles. The course provides students with practical experience in various self-driving vehicles concepts such as machine learning and computer vision. Concepts such as lane detection, traffic sign classification, vehicle/object detection, artificial intelligence, and deep learning will be presented. The course is targeted towards students wanting to gain a fundamental understanding of self-driving vehicles control. Basic knowledge of programming is recommended. However, these topics will be extensively covered during early course lectures; therefore, the course has no prerequisites, and is open to any student with basic programming knowledge. Students who enroll in this self-driving car course will master driverless car technologies that are going to reshape the future of transportation.Tools and algorithms we'll cover include:OpenCVDeep Learning and Artificial Neural NetworksConvolutional Neural Networks Template matchingHOG feature extractionSIFT, SURF, FAST, and ORBTensorflow and KerasLinear regression and logistic regressionDecision TreesSupport Vector MachinesNaive BayesYour instructors are Dr. Ryan Ahmed with a PhD in engineering focusing on electric vehicle control systems, and Frank Kane, who spent 9 years at Amazon specializing in machine learning. Together, Frank and Dr. Ahmed have taught over 500,000 students around the world on Udemy alone.Students of our popular course, "Data Science, Deep Learning, and Machine Learning with Python" may find some of the topics to be a review of what was covered there, seen through the lens of self-driving cars. But, most of the course focuses on topics we've never covered before, specific to computer vision techniques used in autonomous vehicles. There are plenty of new, valuable skills to be learned here!
