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How to write a PhD research proposal on ‘deep learning’

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Due to the complexity of the concepts, it is essential to know how to write a PhD research proposal on ‘deep learning’ early enough before the actual writing.

Deep learning is a collection of algorithms in use for machine learning to model the high-level concepts in data using model architectures that are a composition of various nonlinear transformations. It is part of the methods to learn representations of data.  An algorithm is ‘deep’ if the input of data passes through a series of nonlinear transformations before it has become an output.

Deep learning allows computational models with processing layers to learn data representations with various levels of abstraction without the need for manual identification of features. It relies on the available Write my literature review training process to discover the critical patterns in input examples. An example of how to implement deep learning is when online service provider such as Netflix uses it to predict what a customer is going to order.

Organizing a Ph.D. proposal on deep learning

 Begin by familiarizing with deep learning algorithms before writing your organize your ideas in these sections.

Literature review 

A literature review should provide a survey of relating works to clarify the sphere of your work.   Find contemporary publications that relate to your research.  Determine the reason why there is no modern data on the problem if all that you find is old.   Deep learning has many uses, and it could be that some of the relating work might appear in another field. Many people have more interest in using the concepts than addressing it, and it is a challenge for many researchers in this area.

Problem statement

The purpose of this section is to explain the problem to solve in the study. It requires much learning on the current state of deep learning to determine the problems on which the people are focusing. Identify the specific problem to address.

The significance of study

The purpose of this part is to explain the problem and importance of tackling it.  This section should present arguments supporting the relevance of the problem and reasons why anyone should care. It puts the project into context.

Challenges

Explains the difficulties that you will tackle for you to solve the problem.   These challenges can be show stoppers for the project or be irrelevant because they focus on a different aspect. Explain the reason for acknowledging the difficulty but decided to avoid addressing it explicitly.   Describe the ways of resolving or working around all other challenges.

Background

A background of a Ph.D. research proposal provides a summary that helps readers to understand the approach.

Methodology

 A methodology is the method you intend to use for solving, provides a sound validation of a verification method for the approach.  You should be concise on the steps to follow, what you want to achieve, the scope and timeline.

Limitations and delimitations

Explains limitations, delimitations, and assumptions about the way you used when narrowing down the problem. Gauge all the efforts of past researchers in solving the questions using the methods you propose.

Preliminary experiments and results

 The purpose of this section is to explain all the tests, observations and conclusions. It should also analyze the results.

 Bibliography

 A bibliography is the last section that lists the related works and the cited references. You include all of them on this section.

A research proposal is provisional and might change as your study continues. It is still essential to ensure that it is error-free and in a consistent structure before sending it to evaluators.

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