Coursera
在线学位寻找职业企业版面向大学
  • 浏览
  • 顶级课程
  • 登录
  • 免费加入
    Coursera
    • 浏览
    • Reinforcement Learning

    筛选依据

    ''reinforcement learning'的 47 个结果

    • University of Alberta

      University of Alberta

      Reinforcement Learning

      您将获得的技能: Artificial Neural Networks, Entrepreneurship, Euler'S Totient Function, Leadership and Management, Machine Learning, Machine Learning Algorithms, Markov Model, Mathematics, Operations Research, Planning, Reinforcement Learning, Research and Design, Strategy and Operations, Supply Chain and Logistics, Theoretical Computer Science

      4.7

      (2.9k 条评论)

      Intermediate · Specialization · 3+ Months

    • University of Alberta

      University of Alberta

      Fundamentals of Reinforcement Learning

      您将获得的技能: Mathematics, Research and Design, Operations Research, Strategy and Operations, Process, Reinforcement, Reinforcement Learning, Machine Learning

      4.8

      (2.3k 条评论)

      Intermediate · Course · 1-3 Months

    • New York Institute of Finance

      New York Institute of Finance

      Machine Learning for Trading

      您将获得的技能: Accounting, Artificial Neural Networks, Business Analysis, Cloud Computing, Computer Programming, Data Analysis, Finance, Financial Analysis, General Statistics, Investment Management, Machine Learning, Mathematics, Probability & Statistics, Python Programming, Reinforcement Learning, Statistical Programming, Trading

      3.9

      (930 条评论)

      Intermediate · Specialization · 1-3 Months

    • New York University

      New York University

      Machine Learning and Reinforcement Learning in Finance

      您将获得的技能: Applied Mathematics, Calculus, Computer Programming, Finance, General Statistics, Investment Management, Machine Learning, Machine Learning Algorithms, Markov Model, Mathematics, Probability & Statistics, Python Programming, Reinforcement Learning, Statistical Programming, Theoretical Computer Science

      3.7

      (741 条评论)

      Intermediate · Specialization · 3+ Months

    • IBM

      IBM

      Deep Learning and Reinforcement Learning

      您将获得的技能: Deep Learning, Machine Learning, Python Programming, Computer Vision, Computer Programming, Statistical Programming, Artificial Neural Networks, Reinforcement Learning

      4.6

      (95 条评论)

      Intermediate · Course · 1-3 Months

    • DeepLearning.AI

      DeepLearning.AI

      Deep Learning

      您将获得的技能: Algorithms, Applied Machine Learning, Artificial Neural Networks, Bayesian Statistics, Big Data, Communication, Computer Graphic Techniques, Computer Graphics, Computer Programming, Computer Vision, Convolutional Neural Network, Data Management, Deep Learning, Entrepreneurship, General Statistics, Human Computer Interaction, Interactive Design, Linear Algebra, Machine Learning, Machine Learning Algorithms, Mathematical Optimization, Mathematical Theory & Analysis, Mathematics, Natural Language Processing, Probability & Statistics, Python Programming, Regression, Statistical Machine Learning, Statistical Programming, Strategy and Operations, Theoretical Computer Science

      4.8

      (132.4k 条评论)

      Intermediate · Specialization · 3+ Months

    • Placeholder
      New York University

      New York University

      Reinforcement Learning in Finance

      您将获得的技能: Machine Learning

      3.6

      (118 条评论)

      Advanced · Course · 1-4 Weeks

    • Placeholder
      Google Cloud

      Google Cloud

      Reinforcement Learning: Qwik Start

      Beginner · Project · Less Than 2 Hours

    • Placeholder
      University of Pennsylvania

      University of Pennsylvania

      AI For Business

      您将获得的技能: Applied Machine Learning, Big Data, Computational Thinking, Computer Programming, Data Management, Database Administration, Databases, Entrepreneurship, Finance, Human Resources, Leadership, Leadership and Management, Machine Learning, Marketing, People Management, Reinforcement Learning, Security Engineering, Software Security, Strategy and Operations, Theoretical Computer Science

      4.6

      (67 条评论)

      Beginner · Specialization · 3+ Months

    • Placeholder

      免费

      University of Washington

      University of Washington

      Computational Neuroscience

      您将获得的技能: Mathematics, Python Programming, Computer Programming, Modeling, Marketing, Machine Learning, Data Analysis, Artificial Neural Networks, Neuroscience, Statistical Programming, Probability & Statistics, Reinforcement Learning, Communication, Linear Algebra, Other Programming Languages, Machine Learning Algorithms, Deep Learning, Data Analysis Software

      4.6

      (927 条评论)

      Beginner · Course · 1-3 Months

    • Placeholder

      免费

      Hebrew University of Jerusalem

      Hebrew University of Jerusalem

      Israel State and Society

      您将获得的技能: Culture, Machine Learning, Entrepreneurship, Adaptability, Applied Machine Learning, Business Psychology, Reinforcement Learning, Leadership and Management

      4.7

      (310 条评论)

      Beginner · Course · 3+ Months

    • Placeholder
      University of Alberta

      University of Alberta

      A Complete Reinforcement Learning System (Capstone)

      您将获得的技能: Artificial Neural Networks, Reinforcement Learning, Machine Learning, Reinforcement

      4.7

      (549 条评论)

      Intermediate · Course · 1-3 Months

    与 reinforcement learning 相关的搜索

    reinforcement learning in finance
    reinforcement learning for trading strategies
    reinforcement learning: qwik start
    fundamentals of reinforcement learning
    a complete reinforcement learning system (capstone)
    deep learning and reinforcement learning
    machine learning and reinforcement learning in finance
    overview of advanced methods of reinforcement learning in finance
    1234

    总之,这是我们最受欢迎的 reinforcement learning 门课程中的 10 门

    • Reinforcement Learning: University of Alberta
    • Fundamentals of Reinforcement Learning: University of Alberta
    • Machine Learning for Trading: New York Institute of Finance
    • Machine Learning and Reinforcement Learning in Finance: New York University
    • Deep Learning and Reinforcement Learning: IBM
    • Deep Learning: DeepLearning.AI
    • Reinforcement Learning in Finance: New York University
    • Reinforcement Learning: Qwik Start: Google Cloud
    • AI For Business: University of Pennsylvania
    • Computational Neuroscience: University of Washington

    您可以在 Machine Learning 中学到的技能

    Python 程序设计 (33)
    Tensorflow (32)
    深度学习 (30)
    人工神经网络 (24)
    大数据 (18)
    统计分类 (17)
    代数 (10)
    贝叶斯定理 (10)
    线性代数 (10)
    线性回归 (9)
    Numpy (9)

    关于 强化学习 的常见问题

    • Reinforcement learning is a machine learning paradigm in which software agents use a process of trial and error to learn how to complete tasks in a way that maximizes cumulative rewards as defined by their programmers. In contrast to supervised learning paradigms, reinforcement learning systems do not need labeled input/output pairs or explicit corrections of suboptimal actions; and, in contrast to unsupervised learning, reinforcement learning defines an explicit goal, which is the maximization of the value returned by the Q-learning (or “quality” learning) algorithm as a result of its actions.

      Because it combines the goal orientation of supervised learning with the flexibility of unsupervised learning, reinforcement learning is very important in creating artificial intelligence (AI) applications requiring successful problem-solving in complex situations. For example, they are often used in financial engineering to develop optimal trading algorithms for the stock market. They are also used to build intelligent systems to allow robots and self-driving cars to navigate real-world environments safely.‎

    • As one of the main paradigms for machine learning, reinforcement learning is an essential skill for careers in this fast-growing field. Reinforcement learning is particularly important for developing artificially intelligent digital agents for real-world problem-solving in industries like finance, automotive, robotics, logistics, and smart assistants. According to Glassdoor, the average annual salary for machine learning engineers in America is $114,121 per year, a high level of pay which reflects the high level of demand for this expertise.‎

    • Absolutely. Coursera hosts a wide variety of courses in reinforcement learning and related topics in machine learning, as well as the use of these techniques in applied contexts such as finance and self-driving cars. These courses and Specializations are offered by top-ranked institutions in this field, including the deepmind.ai, New York University, the University of Toronto, and the University of Alberta’s Machine Intelligence Institute. You can learn remotely on a flexible schedule while still getting feedback from expert professors and instructors, ensuring that you’ll get a high quality education with all the reinforcement you need to learn these valuable skills with confidence.‎

    • Because reinforcement learning itself isn't a beginner-level subject, you'll need to have a good grasp on the fundamentals of machine learning before starting to learn it. Additionally, many courses will require you to have a strong background in high-level mathematics such as linear algebra, statistics, and probability. Most courses will require you to be proficient in Python, although people familiar with other programming languages like C++, Matlab, and JavaScript can often use those skills to help them learn reinforcement learning. Having the ability to implement algorithms from pseudocode may be another prerequisite. As you progress, you'll gain skills in using reinforcement learning solutions to solve problems with probabilistic artificial intelligence, function approximation, and intelligent systems.‎

    • People best suited to roles within the reinforcement learning realm should have a passion for machine learning with a drive for analytics and data and an interest in providing frontline support to solve real-world problems while leveraging innate creative problem-solving skills. Additionally, many companies like to see that candidates have strong communication skills and the ability to collaborate across disciplines and departments. There are a variety of roles associated with reinforcement learning, including analysts, engineers, and researchers. In late February 2021, there were more than 1,800 job listings for people proficient in reinforcement learning on LinkedIn.‎

    • If you want to be a part of the future of machine learning, learning reinforcement learning may be a good move for you. This innovative machine learning technique creates an algorithm that learns through trial and error, leading to a combination of short- and long-term rewards such as the ability to define sequences to solve problems using a reward-based learning approach. It's useful across multiple industries, including the tech industry, business, advertising, finance, and e-commerce, all of which find reinforcement learning useful in part because of its ability to offer greater personalization. Ultimately, if you want to work within AI and machine learning, this could be a step to advancing your goals.‎

    此常见问题解答内容仅供参考。建议学生多做研究,确保所追求的课程和其他证书符合他们的个人、专业和财务目标。
    其他可浏览的主题
    Placeholder
    艺术与人文
    338 课程
    Placeholder
    商务
    1095 课程
    Placeholder
    计算机科学
    668 课程
    Placeholder
    数据科学
    425 课程
    Placeholder
    信息技术
    145 课程
    Placeholder
    健康
    471 课程
    Placeholder
    数学和逻辑
    70 课程
    Placeholder
    个人发展
    137 课程
    Placeholder
    物理科学与工程
    413 课程
    Placeholder
    社会科学
    401 课程
    Placeholder
    语言学习
    150 课程

    Coursera Footer

    开拓职业生涯或促进职业发展

    • Google 数据分析师
    • Google 项目管理
    • Google UX 设计
    • Google IT 支持
    • IBM 数据科学
    • IBM 数据分析师
    • 使用 Excel 和 R 的 IBM 数据分析
    • IBM Cybersecurity Analyst
    • IBM 数据工程
    • IBM 全栈云开发人员
    • Facebook 社交媒体营销
    • Facebook 市场营销分析
    • Salesforce 销售发展代表
    • Salesforce 销售运营
    • 直觉簿记
    • 备考 Google Cloud 认证:云架构师
    • 备考 Google Cloud 认证:云数据工程师
    • 开启您的职业生涯
    • 准备证书
    • 开拓职业生涯

    浏览热门主题

    • 免费课程
    • 学习语言
    • python
    • Java
    • 网页设计
    • SQL
    • Cursos Gratis
    • Microsoft Excel
    • 项目管理
    • 网络安全
    • 人力资源
    • 数据科学免费课程
    • 说英语
    • 内容写作
    • 全栈网络开发
    • 人工智能
    • C 语言程序设计
    • 沟通技能
    • 区块链
    • 查看全部课程

    热门课程和文章

    • 适用于数据科学团队的技能
    • 数据驱动的决策
    • 软件工程技能
    • 工程团队所需的软技能
    • 管理技能
    • 营销技能
    • 销售团队所需的技能
    • 产品经理技能
    • 财务技能
    • 英国的热门数据科学课程
    • Beliebte Technologiekurse in Deutschland
    • 热门网络安全证书
    • 热门 IT 证书
    • 热门 SQL 证书
    • 营销经理职业指南
    • 项目经理职业指南
    • Python 程序设计技能
    • Web 开发者职业指南
    • 数据分析师技能
    • 用户体验设计师方面的技能

    在线获得学位或证书

    • MasterTrack® 证书
    • 专业证书
    • 大学证书
    • MBA 和商学学位
    • Data Science Degrees
    • Computer Science Degrees
    • 数据分析师学位
    • 公共卫生学位
    • 社会科学学位
    • 管理学位
    • 欧洲顶级大学学位
    • 硕士学位
    • 学士学位
    • 具有成绩录取途径的学位
    • 学士学位课程
    • 什么是学士学位?
    • 取得硕士学位需要多长时间?
    • 在线获取 MBA 有什么价值?
    • 报名研究生院的 7 种付费方式
    • 查看所有证书

    Coursera

    • 关于
    • 我们提供的内容
    • 管理团队
    • 工作机会
    • 目录
    • Coursera Plus
    • 专业证书
    • MasterTrack® 证书
    • 学位
    • 企业版
    • 政府版
    • 面向校园
    • 成为合作伙伴
    • 新冠疫情响应

    社区

    • 学生
    • 合作伙伴
    • 开发者
    • Beta 测试人员
    • 专业译员
    • 博客
    • 技术博客
    • 教学中心

    更多

    • 媒体
    • 投资者
    • 条款
    • 隐私
    • 帮助
    • 内容访问
    • 联系我们
    • 文章
    • 目录
    • 附属公司
    随时随地学习
    通过 App Store 下载通过 Google Play 获取
    Placeholder
    © 2022 Coursera Inc.保留所有权利。
    • Placeholder
    • Placeholder
    • Placeholder
    • Placeholder
    • Placeholder