[TEA-T3] IDC4U Inter ...

Questions: Plan machine Learning Solutions for your startup company. Ensure your submission falls within the required range of words.

Machines learn from experience, with "experience" represented through data. This data falls into two categories: structured and unstructured. Structured data encompasses databases and spreadsheets, while unstructured data includes emails, work logs, and PDF files. Amassing sufficient data is pivotal for the efficacy of machine learning. In step 4 of the project, you are tasked with developing a strategy to collect internal and public data for your startup. Guided by Porter's Generic Competitive Strategies, carefully consider the datasets you aim to compile. Identify three machine learning applications that could fortify your business's competitive stance. For each application, compose a paragraph (150-250 words) detailing how it could spur your business's growth.

This inquiry-based approach encourages you to explore what kind of machine learning solutions can better help your startup company gain a competitive advantage.

Collaboration Requirement:

To foster collaboration and leverage diverse perspectives within your team, each member (student) must contribute to the assignment based on their assigned role within the fictional organization. Here's how the process should unfold:

Contribution: Each team member must write one case of he/she identified.

Forum Participation: Post your ideas on Activity: Planning Machine Learning Solutions for your startup company in the 'Machine Learning and Its Business Applications ‘Forum of Collaboration Book. Share your thoughts and seek feedback. This is where the collaborative aspect of the assignment comes alive.

Feedback Exchange: After posting your contribution, you must read, reflect, and provide constructive feedback on the posts of at least two other students. This feedback should include suggestions for improvement and positive reinforcement of what you found compelling.

Final Submission: The collective insights, feedback, and discussions from the forum should inform the final submission of your project.

·      Each individual must submit their contribution, consisting of one machine learning use case relevant to your company, detailed in 150-250 words.

·     The CEO, incorporating input from all team members, will compile and refine these submissions into a cohesive document. This document will showcase three machine learning use cases within your company, each described in 150-250 words, for a total of 450-750 words, reflecting the collaborative intelligence of your team.

Download detail requirement.