Deep Learning Research Proposal

Various deep learning project proposals development process includes describing a research-based queries and problems, demonstrating its importance and suggesting an approach to overcome this. Below we discussed about the common flow of deep learning-based project proposals:

1. Title:

• Our title should be effective, clear and brief.

2. Introduction:

• Background: In background study, we offer various research related ideas. What’s the current state of deep learning in the area of our interest?
• Problem statement: Specific problems and issues that we are intended to overcome are properly described in our study. Why is it important?
• Objective: We have to discuss about the major goal of our research.

3. Literature Survey:

• For our specified problem, we described some previous research solutions and techniques.
• We have to point out the research gaps in some techniques or concepts that need further enhancement.
• To inspire our research, initial experimental analysis and results are examined by us.

4. Research Queries and Hypotheses:

• Demonstrate particular queries that we ensure about answer and we will examine hypotheses.

5. Methodology:

• Data: Utilized datasets and the processes involved such as gathering of data, preprocessing and data augmentation are investigated by us.
• Framework: In our study, we discussed about the utilized or constructed neural network framework.
• Training: We investigated about the process involved like model training, loss functions, optimization and regularization methods etc.
• Evaluation: Discussed about how we are going to examine the model’s efficiency. What metrics will we use?
• Software and Hardware: Utilized libraries, tools and computing resources have to be mentioned in our research.

6. Preliminary Findings (if any):

• We can discuss about the basic experimental analysis and results that may inspire our research or it may show its efficiency.

7. Significance and Impact:

• Important objective of our research are investigated by us. Who will benefit from it? How it might it advance the field?

8. Timeline:

• Time utilization for various stages of our project is described in our study.

9. Budget (if applicable):

• We discussed about the calculated cost like data acquisition, computing resources and software licenses.

10. Potential Challenges and Overcoming Plans:

• The defined problems are highlighted and the strategies to overcome are also described by us.

11. Conclusion:

• In conclusion, we explained about the essential aspects of our proposal and its significance is restated.

12. References:

• We should point out all the cited references which include articles, papers and resources.

       Tips:

• Clarity: We need to check whether our project is understandable and free from jargon or not. Even for the people who are not well versed in our research field, it should be interpretable.
• Rigour: The exactness of our proposed techniques and concept is very important.
• Feedback: Look for reviews from professionals, associations, and staffs to confirm about model’s efficiency is an appreciable one before publishing our project.

Often, we consider particular needs and conditions of the association, institution or some research groups in which we are going to submit your project proposals. We follow the rules and instructions properly. Plagiarism free paper will be provided in leading tools like Turnitin we detect plagiarism to assure you success.

Which of these are the research areas covered by deep learning?

            Deep learning has been utilized in various research concepts. We listed out deep learning based innovative fields and sub-fields that we frequently work out and achieve success are listed below:

1. Natural Language Processing (NLP):

• Speech Recognition and Generation
• Question-Answering
• Language Modeling (for instance: Transformers)
• Named Entity Recognition
• Sentiment Analysis
• Text Summarization
• Machine Translation