CS计算机代考程序代写 python Excel Submission Instrucons

Submission Instrucons
This coursework consists of a group project divided into two parts with different weights:
– Part (1) consists of a group report on a specific machine learning project. The final deliverable consists of a single PDF file and a zip file with the code. The deliverable includes a zip file with the code, and a wrien summary (up to 4500 words) describing soluons, design choices, evaluaon and a reflecon on the main challenges faced during development and insights gained throughout the process.

– Part (2) consists of an individual reflecve essay (up to 1500 words) where students reflect on the main insights gained as part of the group project. Cover sheet should also be submied in this part.
Description
Type
Name
Part 1
Compulso ry
One PDF (.pdf) file
groupreport_[group number].pdf
Part 1
Compulso ry
One ZIP (.zip) file containing the Python code
groupcode_[group_number]. zip
Part 2
Compulso ry
One PDF (.pdf) file for the individual essay
individualessay_[student number].pdf
Cover sheet
Compulso ry
One PDF (.pdf) file (to be submitted with Part 2)
[student number].pdf
Part 1: The group report should be submied in learning central (group assignment) by a nominated team member as a single PDF document and a zip file by 9:30am on Tuesday, June 1st. Prior to handing in make sure all documentaon has been collected. Addional supporng material, such as sources or data may also be submied if appropriate along with the code zip file. Any code submied will be run in Python 3 (Linux) and must be submied as spulated in the instrucons. All team members must have seen and agreed to the final version of the submission. Make sure the report clearly menons your group number, a list of all members of the group (with full name and student id as on learning central), the project tle, and the name of the supervisor on the tle page of your report.
Part 2: The cover sheet will be submied together with the individual report. Both the cover sheet and individual report will be submied in Learning Central by the individual report deadline (i.e. Friday, June 4th at 9:30am).
Any deviaon from the submission instrucons above (including the number and types of files submied) will result in a mark of zero for the assessment or queson part.
Staff reserve the right to invite students to a meeng to discuss coursework submissions
Assignment
In this coursework, students demonstrate their familiarity with the topics covered in the module via a group project.
Marks will be awarded to the individual student based on the quality of the group report and their contribuon and the individual report. All students should contribute to the group projects

– extenuang circumstances submied for the spring term project period will be considered pro-rata for the contribuon and for an extension on the individual essay.
Your submission must include the official Coursework Submission Cover sheet, which can be found here:
hps://docs.cs.cf.ac.uk/downloads/coursework/Coversheet.pdf
Any deviaon from the submission instrucons above (including the number and types of files submied) may result in a mark of zero for the assessment or queson part.
Staff reserve the right to invite students to a meeng to discuss coursework submissions.
Part 1: Group report
In Part 1, students will be allocated in groups to design a machine learning project in one specific topic. The list of all topics along with their descripons is available in the following link: hps://docs.google.com/document/d/1P8jc81L_HW3DDdZaIMfMcekrPeDYuBm-2qTC7knbKV8/ edit?usp=sharing
Each group will be composed of roughly 5-7 students and will be assigned a specific dataset and a supervisor. The task of each group consists of developing a whole machine learning pipeline that aempts to solve the task. The usage of neural networks as methods/baselines is not mandatory but will be posively assessed; the non-usage of neural methods should be properly jusfied.
Throughout the course the groups should present their progress to their supervisor each session. Finally, the group will write a report summarizing the steps followed and the main insights gained as part of the process.
As part of the group decisions, each student will be allocated to one of the following tasks:
– Descripve analysis of the dataset + Error analysis
– Preprocessing + Literature review
– Implementaon + Results
Each of these tasks will have a minimum of two students involved (except in exceponal cases when this is not possible), who will work together in the specific task and as part of the group. The structure of the report will be decided by the group members. In the following link, students can find some guidelines to write the report, including some of the common secons

that groups may want to include in their report:
hps://docs.google.com/document/d/1ku-K6mBH8-Wdfy_Dz_gvpReDv6knWCFxq4rsMDCrPHY/ edit?usp=sharing
Note: These are just guidelines and students are not forced to follow this structure. New secons may be added or adjusted if necessary.
Each student will also be involved in all group acvies/tasks and will be responsible for the well funconing and coordinaon of the team members.
Deliverables
The deliverables for this part includes a report of no more than 4500 words and a zip file with
the Python code. The code should contain three specific parts:
(1) Code to get the stascs used to complement the descripve analysis of the dataset.
(2) Code to train one of the best performing models in the training set and evaluate it in the test set. This code should also include all steps for preprocessing the original dataset, if it
were necessary.
(3) A README file explaining how to run the code for each of the two parts.
The code will not be marked separately and will only be used as a complement to assess specific parts of the report.
Assessment
The final mark for this part (75% of the total marks) will result from the following items:
– Descripve analysis of the dataset + Error analysis (15%)
– Preprocessing + Literature review (15%)
– Implementaon + Results (15%)
– Student¡¯s own allocated task from the three above (15%)
– Group report as a whole, including its coherence and structure (15%)
Note: In addion to the specific individual task assigned, in some cases marks might be weighted by the individual contribuon in the project. This would be based on collected evidence.
All main criteria carry equal weight as indicated above for your total mark and will be evaluated on the following scale:
**Excellent** (70-100%): rigorous, methodical, analyc, content meets all requirements of the work, very few errors/omissions.

**Good** (60-69%): competent, reasoned, coherent, content very sound, few errors/omissions.
**Fair** (50-59%): sasfactory, relevant, content meets many of the required elements, some errors/omissions.
**Fail** (1-49%): not passable, evident weaknesses, gaps in content, evident errors/omissions. **None** (0%): indicates that the topic has not at all been covered.
Part 2: Individual reflection essay
In Part 2, students are asked to write a reflecve essay about their group projects. The individual essay must discuss your contribuon to the group report and to the overall group work. You must show that you contributed to the group work, which will be determined via the individual report and the contribuon monitoring, conducted by the supervisor, if it were necessary. Discuss what tasks you have performed and provide evidence of your work (you may refer to the group report for the actual work/results). Discuss how you approached these tasks and how you interacted with other members, both in sharing your results and in organising the team’s acvies. Consider how well your exisng skills were ulised and what new skills you have learned. Then reflect on your overall performance and role in the team and suggest what went well and what changes you will be making to improve (1) your performance in parcular, and (2) the performance and results of methods and analyses performed as part of the project. You may also reflect on how your perspecve and approach changed over me and adapted to improve your work.
Note: Please indicate the informaon about your group (group number, project name) in a visible place at the top of your essay.
The individual report must have no more than 1500 words. It does not have to be exhausve, but should contain good examples of what you have done and discuss key aspects. This part weighs 25% of the total marks.
Learning Outcomes Assessed
This coursework covers all LOs listed in the module descripon.

Criteria for assessment
Criteria for each individual part is provided separately. The final mark will be obtained from a weighted sum of the two parts: Part 1 – 75%; Part 2 – 25%.
The grade range is divided in: Disncon (70-100%)
Merit (60-69%)
Pass (50-59%)
Fail (0-50)