Java代写：INFO3406 Data Analytics代做

代写Data Analytics作业，从数据清洗，分析数据，模型预测，到展示结果。Learning OutcomesThe objective of the project is to put in practice all the theory learned in class with a tool and methodology that help students in their future as professionals.Specifically the learning outcomes are,Process large data sets using appropriate technologiesSelect statistical techniques appropriate for summarization and analysis of a data set, and can justify their choiceSelect statistical techniques appropriate for evaluation of a predictive model that is based on data analysis, and can justify their choiceFind out details of how to use a method or tool in the data analytic process.Carry out (in guided stages) the whole design and implementation cycle for creating a pipeline to analyse a large heterogeneous dataset.Apply concepts and terms from social science to describe and analyse the role of a data analysis task in its organizational contextCommunicate the results produced by an analysis pipeline, in oral and written form, including meaningful diagramsCommunicate the process used to analyse a large data set, and justify the methods used.The ProjectIn this project the students have to follow the CRISP-DM methodology to achieve a specific goal, using data analytics contents and tools learned in this course.The project is divided in four stages.Project Stage 1: Obtain data, clean it and load it.Project Stage 2: Summarize and analyse the data.Project Stage 3: Develop and test a predictive model.Project Stage 4: presentation of results.Each stage in detail,Project Stage 1: Obtain data, clean it and load itBusiness UnderstandingDetermine Business ObjectivesBackgroundBusiness ObjectivesBusiness Success CriteriaAssess SituationInventory of ResourcesRequirements, Assumptions, and ConstraintsRisks and ContingenciesTerminologyCosts and BenefitsDetermine Data Mining GoalsData Mining GoalsData Mining Success CriteriaProduce Project PlanProject PlanInitial Assessment of Tools and TechniqueData UnderstandingCollect Initial DataInitial Data Collection ReportDescribe DataData Description ReportProject Stage 2: Summarize and analyse the dataData UnderstandingExplore DataData Exploration ReportVerify Data QualityData Quality ReportData PreparationSelect DataRationale for Inclusion/ ExclusionClean DataData Cleaning ReportConstruct DataDerived AttributesGenerated RecordsIntegrate DataMerged DataFormat DataReformatted DataDatasetDataset DescriptionProject Stage 3: Develop and test a predictive modelModelingSelect Modeling TechniquesModeling TechniqueModeling AssumptionsGenerate Test DesignTest DesignBuild ModelParameter Settings ModelsModel DescriptionsAssess ModelModel AssessmentRevised Parameter SettingEvaluationEvaluate ResultsAssessment of Data Mining Results w.r.t. Business Success CriteriaApproved ModelsReview ProcessReview of ProcessDetermine Next StepsList of Possible Actions DecisionProject Stage 4: Presentation of resultsDeploymentPlan DeploymentDeployment PlanPlan Monitoring and MaintenanceMonitoring and Maintenance PlanProduce Final ReportFinal Report Final PresentationReview ProjectExperience Documentation本团队核心人员组成主要包括硅谷工程师、BAT一线工程师，精通德英语！我们主要业务范围是代做编程大作业、课程设计等等。我们的方向领域：window编程 数值算法 AI人工智能 金融统计 计量分析 大数据 网络编程 WEB编程 通讯编程 游戏编程多媒体linux 外挂编程 程序API图像处理 嵌入式/单片机 数据库编程 控制台 进程与线程 网络安全 汇编语言 硬件编程 软件设计 工程标准规等。其中代写编程、代写程序、代写留学生程序作业语言或工具包括但不限于以下范围:C/C++/C#代写Java代写IT代写Python代写辅导编程作业Matlab代写Haskell代写Processing代写Linux环境搭建Rust代写Data Structure Assginment 数据结构代写MIPS代写Machine Learning 作业 代写Oracle/SQL/PostgreSQL/Pig 数据库代写/代做/辅导Web开发、网站开发、网站作业ASP.NET网站开发Finance Insurace Statistics统计、回归、迭代Prolog代写Computer Computational method代做因为专业，所以值得信赖。如有需要，请加QQ：99515681 或邮箱：99515681@qq.com 微信：codehelp