In the field of machine learning, how to write a good academic thesis _ paper

When you do a research job and you are ready to share it with your colleagues, one of the first tasks is to turn your work into an article. The question is, how to write a quality article. We take the application of machine learning field as an example to explore the problem of paper writing. Note that any good article should be based on good research work, we do not talk about the quality of your research work, only discuss the writing problem of the article. To write a job clearly, be sure to think about it first, or what you write. So don't rush to write, let's think first. Think what. First of all, ask yourself 10 questions, if the 10 questions are already clear, then it is time to shoot. Otherwise, I personally suggest you take a break first. or write it in vain. What are the 10 questions?

Question one: What problem do you want to solve?

Question two: Why is the question you want to solve is important and meaningful.

Question three: What are the challenges and difficulties in this issue?

Question four: Who else has solved similar or related problems?

Question five: how they do it.

Question six: How do you deal with these challenges?

Question seven: What is the difference between your methods?

Question eight: Why do you think your method is better than others '?

Question nine: Is there any evidence to prove that your method is really good.

Question 10: What are the conclusions and limitations of your work?

Looks like a lot of wordy, doesn't it? We will soon say that any answer to any question is likely to make your article into a heartbreaking rejection letter. On the other hand, your article is actually answering these questions from beginning to end. Generally speaking, an article is divided into several common parts as follows. Title, abstract (abstract), Introduction (Introduction), related work (Related Work), problem definition (Problem formulation), problem solving (our Solution), Experiment (experiments), discussion (Discussion), conclusions and next steps (conclusion and Future Work), appendix (appendix), others (keyword-keywords, article category-category, Index-Reference).