|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/detect-market-status-with-ai/
课程评论：没有评论
课程名称：懒惰交易第6部分：用AI检测市场状态 课程概述： 懒惰交易系列课程旨在结合算法交易的迷人体验，同时学习计算机和数据科学。重点在于构建决策支持系统，以帮助自动化与交易相关的繁琐流程，同时学习数据科学。通过执行基础数据周期（数据输入-数据处理-分析-输出），将构建几个算法。整个7门课程中提供的示例将展示如何构建一个能够在没有太多人工输入的情况下自动进化的综合系统。 课程内容简介： 本课程将使用深度学习分类模型，运用人工智能来分类金融资产的市场状态。学习内容包括： - 使用R和h2o机器学习平台训练监督式深度学习分类模型 - 轻松收集和编写金融资产数据 - 操作数据并构建分类深度学习模型 - 使用随机神经网络结构 - 生成市场类型分类输出以供交易系统使用 - 获取能够在策略中考虑市场状态信息的交易机器人 本项目包含多个短课程，旨在帮助您管理自动化交易系统，包括： - 设置家庭交易环境 - 设置交易策略机器人 - 设置自动化交易日志 - 统计自动化交易控制 - 阅读新闻和情感分析 - 使用人工智能检测市场状态 - 构建AI交易系统 课程更新：已创建专用R包“lazytrade”，以便于不同课程之间的代码共享。所有课程将包括“快速部署”部分以及包含理论解释的部分。 学习目标： 除了交易，完成这些课程还将让您学到更多： - 学习和实践使用决策支持系统 - 通过版本控制和自动统计分析保持组织和系统性 - 学习使用R进行数据读取、处理和机器学习，包括深度学习 - 学习和实践数据可视化 - 学习情感分析和网页抓取 - 学习Shiny在数小时内部署任何数据项目 - 提高生产力技巧 - 学习自动化任务及其调度 - 获取可扩展的MQL4和R代码示例 课程的局限性： 本课程不将详细教授特定的编程概念，不旨在教授数据科学或交易的基础知识，并且不保证代码无错误。 免责声明： 交易存在风险。本课程不应被视为财务建议或服务。过去的结果不能保证未来的表现。您可能需要投入大量时间以重现所提出的方法和概念。
About the Lazy Trading Courses:This series of courses is designed to to combine fascinating experience of Algorithmic Trading and at the same time to learn Computer and Data Science! Particular focus is made on building Decision Support System that can help to automate a lot of boring processes related to Trading and also learn Data Science. Several algorithms will be built by performing basic data cycle 'data input-data manipulation - analysis -output'. Provided examples throughout all 7 courses will show how to build very comprehensive system capable to automatically evolve without much manual input.Inspired by:"it is insane to expect that one system to work for all market types" // -Van K. Tharp"Luck is what happens when preparation meets opportunity" // -Seneca (Roman philosopher)About this Course: Use Artificial Intelligence in TradingThis course will cover usage of Deep Learning Classification Model to classify Market Status of Financial Assets using Deep Learning:Learn to use R and h2o Machine Learning platform to train Supervised Deep Learning Classification ModelsEasily gather and write Financial Asset Data with Data Writer RobotManipulate data and learn to build Classification Deep Learning ModelsUse random neural network structuresFunctions with examples in R packageGenerate Market Type classification output for Trading SystemsGet Trading robot capable to consider Market Status information in your Strategies This project is containing several short courses focused to help you managing your Automated Trading Systems:Set up your Home Trading EnvironmentSet up your Trading Strategy RobotSet up your automated Trading JournalStatistical Automated Trading ControlReading News and Sentiment AnalysisUsing Artificial Intelligence to detect market statusBuilding an AI trading systemUpdate: dedicated R package 'lazytrade' was created to facilitate code sharing among different coursesIMPORTANT: all courses will have a 'quick to deploy' sections as well as sections containing theoretical explanations.What will you learn apart of trading:While completing these courses you will learn much more rather than just trading by using provided examples:Learn and practice to use Decision Support SystemBe organized and systematic using Version Control and Automated Statistical AnalysisLearn using R to read, manipulate data and perform Machine Learning including Deep LearningLearn and practice Data VisualizationLearn sentiment analysis and web scrappingLearn Shiny to deploy any data project in hoursGet productivity hacksLearn to automate your tasks and scheduling themGet expandable examples of MQL4 and R codeWhat these courses are not:These courses will not teach and explain specific programming concepts in detailsThese courses are not meant to teach basics of Data Science or TradingThere is no guarantee on bug free programmingDisclaimer:Trading is a risk. This course must not be intended as a financial advice or service. Past results are not guaranteed for the future. Significant time investment may be required to reproduce proposed methods and concepts
