The project will have a purpose and a story behind that purpose.
The project will have a purpose and a story behind that purpose. It will have solid implications underlined in the final report. please make use of the data analytics to come up with a proper solution to a problem or an answer to a question with appropriate tools. Use jupyter, Excel, ML models.
The datasets are also attached below which should be used for this work.
link(dataset): https://www.theindegenous.org/home/indian-indigeno…
Objectives:
Develop an understanding of the fundamental concepts of big data and machine learning.
Apply Exploratory Data Analysis concepts leveraging the Python programming language and the Jupyter Integrated Development Environment.
Develop and articulate results from Supervised and Unsupervised Python Machine Learning models, including correctly identifying algorithms appropriate for the assigned data set.
Apply skills to real-world case study problems and develop Machine Learning models to solve problems.
Instructions:
The project will have purpose and a story behind that purpose. It will have solid implications. Please make use of appropriate data analytics techniques to come up with a proper solution to a problem or an answer to a question. The task is to write a report and summarize the data set focusing on the variables, data source(s), the target variable(s), the approach to working with this data, and the analytic approach.
The final report is expected to be free from grammatical/spelling errors. The minimum requirement for the report is 2000 words. The report will be double-spaced with 1-inch margins, using Times Roman 12-point font. Project report will outline the methodology, key findings of the statistical analysis as well as the suggestions for how the intended audience should make use of the findings. the project report should include the title, abstract, as well as the table of contents. Please include the bibliography in last pages of the report. The project report should include at least 4-6 charts and the Python code as an appendix. The project report should also contain a data dictionary. The final report should also contain an AI appendix which should be submitted as a separate document. The report will be submitted to a software that checks for plagiarism, Turnitin. In the report/presentation file, do not devote a lot of space to discussions of dead-ends, the pursuit of unproductive ideas, technology problems, etc.
Project Presentation:
Prepare 10-15 slides introducing project, explaining methodology, key findings of statistical analysis and recommendation(s) about what action should be taken based on the findings. The presentation will be intended to the audience of customers who may be interested in hiring you to implement the solutions you are presenting. Design the project presentation accordingly –focus on the solutions and the advantages/benefits the solution may offer to customers. Do not devote a lot of space to discussions of dead-ends, the pursuit of unproductive ideas, technology problems, etc. in the presentation.
Rubric:
Business Understanding / Problem Statement:
Clear, concise, specific question(s) posed, supported by appropriate discussion. Full description of the problem or area of interest, data set, and the plan of analysis is effectively explained. The report demonstrates initiative in carrying the project out.
EDA / Data Understanding & Data Preparation:
Practical EDA conducted for the data set and results provided. Results concisely explained / summarized. For each data set, research variable is described fully, using central tendency and dispersion measures, includes interpretation of what they indicate.
Modeling / Methods:
Statistical methods were fully and correctly applied. Clear explanation of why variables were selected. Includes appropriate, well-labeled, accurate results of the analysis. All conditions are checked correctly for any inference procedures. Satisfied all of the modeling project requirements outlined in the instructions.
Evaluation / Discussion:
Results and discussion are well focused on the questions and included all important points. The conclusion includes a clear answer to the analytics question that is consistent with the data analysis. Justifies key results and procedures, explains assumptions and reasons. Discussion of results is insightful; adds meaning and significance to the report: no unwarranted conclusions.
Report Organized:
Report should follow CRISP-DM Methodology. Ideas support the Business Understanding and presented well. Report is exceptionally well organized and well written, with all charts and tables.
Tone / Font / Style / Format:
Report should contain 2000 words, double-spaced with 1-inch margins, using Times Roman 12-point font. Free from typo errors
To Do List:
Please submit all 6 documents
1. documentation file
2. data dictionary file
3.data file
4. AI appendix file
5. presentation file(please also include each slide explanation in a separate word file for understanding).
6.Python codes and their outputs.(ipynb)
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