Drinkable vs. Undrinkable Bottles
Abstract title is bold font size 11 pt, Times New Roman. The abstract text should have a single line spacing in font size 10 pt, Times New Roman. The abstract provides a concise overview of your work. It should not exceed 250 words. It should contain the highlights of the major parts of the report, including the objective, results, conclusions and recommendations. No details should be included. The information must be communicated in such a way that the reader can understand what was done, and what the outcome was, without having to read the rest of the report. The abstract should be written completely in textual form-that is, in sentences. It should not include equations or references to anything else in the report. It should read smoothly and coherently, not like a collection of sentences from different parts of the report. When the report describes results from several short experiments, the abstract should not resemble several small abstracts of the individual experiments, but must provide smooth transitions between them. Although the abstract is placed at the beginning of the report (for easy access by the reader), it should be written last, after the rest of the report has been completed.
In around 500 words, describe the problem that your team is trying to solve in a clear and concise paragraph. You are also required to identify the motivation behind the project. Why design a solution? How will this make the world better? What are the benefits? And possible uses?
In this section, describe to the reader how the system work/is-designed and the process followed to reach the final results. This section should include two subsections, data collection and AI model, with figures, tables, derivations, calculations, algorithms describing/detailing/designing the overall system. You are expected to write 1000 words per team member in this section.
2.1 Data Collection
This subsection should include multiple paragraphs describing the data collection protocol.
How did you collect the data?
How did you ensure data quality?
How is your data distributed between the classes?
How did you vary the data?
Did you augment the data? How?
How hard easy was it to collect the data? What did you learn and what would you do differently?
Include a montage of samples of your data, and a histogram to show the data distribution between the classes.
2.2 AI Model
In this section, discuss and analyze the results obtained during your research about the AI Model behind Teachable Machine for each problem. Include a sketch of the model and its layers
3. RESULTS, ANALYSIS AND INTERPRETATION OF DATA
This section is devoted to your interpretation of the outcome of the experiment or project. It should include paragraphs with pictures, tables, measurements, and performance evaluations obtained through testing. Tabulate the results against the hyperparameters.
How did you select the hyperparameters?
What cross validation method did you use?
How did you calculate your final results? What did you observe?
What performance criteria have you used?
You are required to write 1000 words per team member in this section.
In this section, summarize the entire report in around 500 words. Base all conclusions on your actual results. Explain the meaning of the experiment and the implications of your results. Examine the outcome in the light of the stated objectives. Seek to make conclusions in a broader context in the light of the results. What did you learn? What would you do differently next time?
Attachment:- Project Template.rar