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      代做BSAN3212、代寫c/c++,Python程序語言

      時間:2024-08-16  來源:合肥網hfw.cc  作者:hfw.cc 我要糾錯



      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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