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        代做BSAN3212、代寫c/c++,Python程序語言

        時(shí)間:2024-08-16  來源:合肥網(wǎng)hfw.cc  作者:hfw.cc 我要糾錯(cuò)



        Deep Learning For Business
        Assessment 1 Guidelines
        Deep Learning for Business Essay
        Instructions
        BSAN**12 - Deep Learning for Business 2
        Task Description:
        The use of deep learning methods and increasingly being adopted across various sectors of the
        economy, and as a result, business and society are likely to undergo significant changes.
        In a 2000-word essay, explore how business and society are likely to respond to these changes and
        what adaptations they may need to make to thrive in this new environment.
        Consider both the potential benefits and challenges of deep learning and the ethical considerations
        that must be considered.
        In your essay, provide specific examples of how deep learning is currently being used in various
        industries and speculate on how these applications may evolve in the future.
        A1 Marking rubric
        BSAN**12 - Deep Learning for Business 3
         Depth and breadth of research = 80 pts
         Required components = 10 pts
         Report professionalism, structure and quality = 10 pts
        Total = 100 pts
        Recommended Report Structure
        BSAN**12 - Deep Learning for Business 4
        1. Title and Introduction
         Create a short title that highlights the key point(s) in your essay.
         Provide a brief overview of deep learning and its significance in various sectors.
         Introduce the purpose and scope of the essay.
        2. Business Response to Deep Learning
         Explain how businesses are embracing deep learning and its potential impact on
        operations.
         Provide specific examples of how deep learning is currently being used in different
        industries.
        Recommended Report Structure (cont  d)
        BSAN**12 - Deep Learning for Business 5
        3. Adaptations Required by Businesses
         Discuss the adaptations businesses may need to make to implement deep learning
        effectively.
         Include suggestions on upskilling the workforce and ensuring data security and privacy.
        4. Society's Response to Deep Learning
         Explore how society is likely to respond to the widespread adoption of deep learning.
         Address concerns related to job displacement and access to technology.
        5. Ethical Considerations
         Discuss the ethical considerations that must be considered when using deep learning.
         Provide recommendations on how businesses and society can address biases and
        ensure responsible AI deployment.
        Recommended Report Structure (cont  d)
        BSAN**12 - Deep Learning for Business 6
        6. Current Applications and Future Speculations
        Highlight current use cases of deep learning in various industries.
         Speculate on how these applications might evolve in the future.
         Support your speculations with emerging trends and technologies in the AI field.
        7. Conclusion
         Summarise the key points discussed in the essay.
         Emphasise the transformative impact of deep learning on business and society.
         Provide a forward-looking statement on the future of deep learning and its implications.
        Suggestions
        BSAN**12 - Deep Learning for Business 7
         Research Thoroughly: Start by conducting in-depth research on deep learning, its
        applications, benefits, and challenges. Use various credible sources, including academic
        papers, industry reports, and news articles.
         Incorporate Real-World Examples: Support your arguments with concrete examples of
        how deep learning is used in different industries. Use case studies to illustrate its
        potential impact on businesses and society.
         Balance Pros and Cons: Present a balanced perspective on deep learning by discussing
        its potential benefits and challenges. Acknowledge any limitations or ethical concerns
        associated with the technology.
        Suggestions
        BSAN**12 - Deep Learning for Business 8
         Structure the Essay Logically: Ensure your essay follows a coherent structure, with each
        section logically flowing into the next. Use subheadings to improve readability and
        organisation.
         Use Clear and Concise Language: Write clearly and concisely, avoiding jargon and
        technical language unless necessary. Aim for clarity and readability.
         Cite Sources Properly: Give credit to the authors of your sources by citing them properly
        (APA 7th).
         Revise and Edit: Before submitting the final essay, thoroughly revise and edit your work
        for clarity, coherence, and grammar errors.
        Submission Checklist
        BSAN**12 - Deep Learning for Business 9
         Title page including title of the essay, student name and student number, and assignment
        word count.
         Table of Contents page.
         The page number is included as a footer on each page.
         Report style format (with subheadings, e.g.,   1.0 Introduction  ) is used.
         1.5 spacing, with 2.5cm margins.
         Consistent font throughout, including headings.
         The essay is within 2,000-word limit (references and appendices are not included in the
        word count).
        Submission Checklist
        BSAN**12 - Deep Learning for Business 10
         APA 7th referencing is followed consistently across all references (in-text and in the
        reference list).
         The essay has been proofread and checked for spelling, and grammatical errors.
         Understand the marking rubric.
         The essay is submitted on time.
         Similarity check (via Turnitin) has been reviewed.
         The essay is written in English.
        Final notes
        BSAN**12 - Deep Learning for Business 11
         This assignment may require a fair bit of time and effort.
         The good news is that spending time on the research now will save you time with your
        final assignment (A3  C Deep Learning Project Proposal).
        CRICOS 00025B
        See you next week!
         TEQSA PRV12080

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