Programming Homework Help. Cortiva Institute Features Help to Predict Golden Spent for Players in Match Discussion
choose a dataset satisfying the requirement and then write a proposal based on the dataset
Hi, so here is the requirementThere are two modalities for this project. You may choose one: • Choose at least one data set from any public source of your choice, a problem associated with that data set, and carry out an interesting analysis. Ultimately, the emphasis should be on prediction, so make sure you conduct your analysis in such a way that you can measure how accurate your forecasts are. • Alternately, choose an active kaggle competition (https://www.kaggle.com/competitions ). In this case, the problem and relevant data set(s) are provided at Kaggle site. Your focus is essentially in tackling the problem with a technique or combination of techniques covered in this class.
The first step in completing the project proposal is to decide on which modality you will work under and select your dataset and problem or a specific Kaggle competition. Remember that the dataset should be large (at least 400,000 observations and at least 15 naturally observed variables excluding response variables – note that if image or other encoded data are used then number of columns are likely to very high) and complexity of the project should be commensurate with the team’s size.Finally write up a short proposal and submit it. The structure of this proposal report document will be as follows: A. Cover Page: Provide Title and name of group participants. [DO NOT WRITE instructor’s name] B. Executive Summary: This will introduce the objective(s) of the project. C. Introduction: Briefly describes the problem, the dataset(s) and the first technique to be applied to develop predictive model. At this stage this section can be short. D. References: Use APA style for in-text citations and listing these cited all articles (books, journal articles, trade publications, and applicable web sites). Avoid citation of programmer or user written webpages or websites for technical content, instead refer to original source such as books or journal/ trade articles.
