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Read-Research-Paper

Research Paper Reading Approach - A notes from Andrew Ng Lecture.

How to Read the Research Paper.

Compile the List of papers.

  • Arxiv Sanity.
  • paperwithcode
  • research gate
  • DeepMind
  • Twitter
  • ML sub reddit
  • NIPS/ICML/....

GOAL

Read 50-100 Research paper to have very good understanding of that Domain.

How to Read One Paper

Multiple Passes.

        1. First pass --- Title/abstract/Figures.
        2. Intro -- Conclusion -- Figures -- skim rest.(skim the related work)
        3. Read the paper but skip the Maths.
        4. Real the whole thing but skip the part that doesn't make sense.
        5. what did the authors tried to accomplish ?
        6. what are the key Elements of the approach ?
        7. what can you use yourself ?
        8. what other references do you want to follow ?

More details on how ?

How to read research papers?

• Ask questions before you start
• What is the motivation?
• What is the problem?
• What is the solution?
• What experiments are done?
• How is the solution evaluated?
• What are the contributions?
• Future direction?
• Relation with existing works?

How to read research papers?

• A one-time reading is not going to work
• Multiple iterations

4+ step process

• Step 1:

• Read the title
• Scan all the sections

• Outcome
• It will give you an idea what the paper is about

4+ step process

• Step 2:

• Read the abstract
• Scan all the sections again
• Look for figures about the method
• Read the conclusion

• Outcome
• It will give you an idea about
• The problem being solved
• A bit about the approach

4+ step process

• Step 3:

• Read the abstract again
• Read the introduction
• Read the overview of the approach
• Try to understand the method from the main figure
• Look for the results which are shown

• Outcome

• Better understanding of the problem
• More insights into the solution
• Evaluation

4+ step process

• Step 4:

• Read method very carefully
• You can skip alien words
• Try to understand as much as you can
• Go through the evaluation carefully

• Outcome

• You should have a better understanding of the paper now
• If you didn’t understand some part of the paper
• Now is the time to look into it

Deeply Understand paper For Maths.

  • Read and take Detailed Notes and then see if you can re-derive it from scratch.(Good Practice -- Give the ability to generalize, to derive new Novel pieces of Math yourself.)

  • Code :

            Run Open-source code.(it's Easy)
        Re-implement from scratch(it gives proper verification that you understand it completely).

Advice On Navigating Career

GOAL

  • JOB (Big company OR STARTUP)(Do imp work)
  • PHD

How to Get a position or Job Offer

  • Selecting a Postion.

what Recruiters Look for

  • Skills(ML,Quiz,Coding)
  • Meaningful Work(Assure that you can work)

Area's of Machine Learning

  • ML

  • DL

  • NLP --- Go depth in any one of this content.(Practical Experience by working on it.)

          Project
      Open-sourced
      research
      Internship

  • CV

  • Recommendation System -- Netflix

  • RL

Do 2-3 Good Project from area's of machine learning.

Weekends -- you have a choice for all your life.It will make you more capable.

  • Read paper
  • Work on paper
  • Open source

Selecting A JOB

  • Work with great people/projects.
  • Focus on the Team (10-30 person) you will interact.
  • Not on Brand.

Job Offer Not Attractive

  • They refuse to say who your manager is.
  • They refuse to say which project you gonna work.
  • Be careful.

Some Company with NO brands but Elite Team

  • Manage to track down the Team.
  • Team is elite dont bother about the brand.
  • Important thing is to do Important Work not on Brand.

General Advice in your Career.

  • Learn the Most.

  • Do Important Work.

                  All these will help in long term.

AI as an Enterprise

  • AI - Artificial Intelligence
  • AGI - Artificial General Intelligence.
  • ANI - Artificial Narrow Intelligence.

True AI Company

  • It requires a good sound company-wide the AI Strategy.
  • Should have In-house AI resources and the AI talents to build sequences of AI Projects.
  • Technical Infrastrucutre to collect the data ,essentilize the data resources as and make the data be an IOT database unified data warehouses(Centralised Data warehouses.).
  • AI workflows and process.
  • Thoughtful regularization.

When someone agrees with your IDEA -- ask them to Gamble on it(nobody knows its right-- so Gamble it).