STAT430作业代写、R课程作业代写、data留学生作业代做、
Final ProjectSTAT430 Spring 2019Due date: May 10, 2019This project aims at applying whatever you have learned from this course and whatever you have learnedfrom other sources for solving real-world problems using complex financial data. Please read the followingitems carefully. Evaluation– Your grade on the project will be calculated based on the group options. Please refer to the groupoptions for the grading details. Dataset– The dataset for the final project has to be the futures data provided in Compass 2g. You can useeither the original tick data or the minutes data provided. There will be bonus credits if chooseto preprocess the tick data by yourself. (Update: If you insist on using some alternative highquality dataset, you have to get my approval in advance.)– The license of the data only allows students who take STAT430: Machine Learning for FinancialData to use the data for their homework and/or projects of the course. PLEASE DELETETHE DATA COMPLETELY AT THE END OF THIS SEMESTER! Grading components– Basic required components create feature matrix and labels conduct analysis involving at least the following components:· fully-connected layers· convolutional neural networks· recurrent neural networks· comparisons of at least 3 models (including shallow machine learning models) that aresignificantly different· commonly used regularization methods such as dropout and regularization the report should include at least the following components:· title, group number, authors, time· a short abstract or executive summary· introduction including but not limited to the objectives of the project· data description / data preprocessing / sources, etc.· exploratory analysis· formal analysis· conclusion– Additional effort The following items will be counted as additional effort:· adding more relevant features (e.g., technical indicators included in R package TTR canbe looked at additional features)· significant effort in tuning hyper-parameters and/or architectures so that the candidatemodel has non-trivial prediction power· any other extra effort based on the instructor’s judgment Project report– The report should be well organized, and the codes and other technical materials should be putinto appendix.– The report can be written in either latex, (R)markdown, or word format, and only a pdf file shouldbe submitted.– There are no requirements on the number of pages of the report. Peer review1– Only applies for the groups with 3 members– Peer reviews will be kept strictly confidential in Compass 2g.– Overall, how efficiently did your group work together on this project.– Evaluate your peer group members, and assign a grade (out of 100) for their contribution andperformance to the project. To be submitted– Group/Individuals: Project report “final-report-[Group number or individual netID].pdf”– Each member from the groups of 3 members: One-page brief peer review “final-peer-[YournetID].pdf”2本团队核心人员组成主要包括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 QQ：99515681 或邮箱：99515681@qq.com 微信：codehelp
