Choosing a Project: My Criteria and Friends' Examples

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Discussion Overview

The discussion revolves around selecting a project for a group assignment, focusing on criteria for project difficulty, feasibility, and personal interest. Participants share their experiences and challenges related to machine learning and the necessary mathematical background, as well as the importance of excitement in project selection.

Discussion Character

  • Exploratory
  • Debate/contested
  • Technical explanation

Main Points Raised

  • One participant outlines criteria for project selection, emphasizing the need for a balance between ease and challenge, as well as the importance of group dynamics and skill levels.
  • Another participant suggests that the project should be engaging and fun to maintain motivation, sharing personal experiences related to project work.
  • A participant expresses uncertainty about their ability to contribute to a machine learning project, despite having studied relevant topics, highlighting concerns about their mathematical knowledge.
  • Feedback is offered by participants with experience in the machine learning industry, indicating a willingness to assist with project-related queries.
  • Concerns are raised about the difficulty of revisiting mathematical concepts necessary for machine learning, with one participant reflecting on their study habits and the challenges of preparing for graduation.
  • Another participant shares their background in statistics and emphasizes the importance of practical experience in machine learning, while also recommending resources for learning.

Areas of Agreement / Disagreement

Participants express varying levels of confidence in their mathematical skills and project capabilities. There is no consensus on the best approach to overcoming challenges related to project selection and mathematical preparation.

Contextual Notes

Participants mention specific challenges related to their educational backgrounds and the need for a solid understanding of mathematics and statistics for machine learning. There are references to personal study habits and the impact of these on current learning efforts.

Who May Find This Useful

Students and individuals interested in project-based learning in machine learning, as well as those seeking advice on balancing project difficulty with personal skills and interests.

shivajikobardan
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My criteria for choosing this project-:
->Should be easy.
->Should be doable in 1.5 months.
->Should not to be too easy and should be just hard enough to be a major project.
->It is a group project but since this is nepal lol mainly 1 person is going to do it. max 2 persons will do this.
->Our skill level is not much. The one who is doing the project knows how to code in django and is good with programming. I personally know the basics of python but I have never made any projects

->We will do projects that have course tutorial. The reason is due to 5) our skill level is not that much so.
these are the types of project our friends are doing for example. if you want to see the complexity of the project that our friends are doing so that you could help us choose it.


Yesterday I asked with 500 projects,today I am asking with around 20 projects, any guidance will be really valuable. If anyone wants full projects list just contact me I will share that.
 
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This is really hard to answer for you. What do you want to do amongst the list? It should feel fun and exciting otherwise you will likely stop wanting to code. I can tell you from experience when the project makes me want to do it versus I have to do it, or it's completely fictitious, the quality of my work is very different. For example, the website MHB is a forum that uses PHP, HTML, CSS, etc. so in order to change something here I need to learn these things at times. That gives me incentive to want to learn them because I have a real problem to solve. In your case this is for a project so it won't be "real" in the same sense, but I think it should be something that excites you. What excites you from the list?
 
Jameson said:
This is really hard to answer for you. What do you want to do amongst the list? It should feel fun and exciting otherwise you will likely stop wanting to code. I can tell you from experience when the project makes me want to do it versus I have to do it, or it's completely fictitious, the quality of my work is very different. For example, the website MHB is a forum that uses PHP, HTML, CSS, etc. so in order to change something here I need to learn these things at times. That gives me incentive to want to learn them because I have a real problem to solve. In your case this is for a project so it won't be "real" in the same sense, but I think it should be something that excites you. What excites you from the list?
we decided to do employee promtion prediction related to machine learning. we have already studied data mining/machine learning. one dude can do this for sure. but i wish that i be able to do it which i am not really hopeful of :(
 
I work in the machine learning industry, I can definitely give feedback if you post here.
 
Jameson said:
I work in the machine learning industry, I can definitely give feedback if you post here.
wow.. you are doing what every students nowadays can only dream of doing...one issue with me is that i was good at math and stuffs. but problem is i have forgotten everything as i didn't make notes. and i am thinking how will i study these 30+ subjects? did this happened to you? i am near graduation and i have only studied my 7th semester properly(i.e i made hipster pdas). i studied other semester like every other student(i didn't make hipster pda short notes for later to revise and neither did i made any good notes)...so to learn machine learning you need to know good amount of math and probability. learning 4 engineering mathematics and 1 semester probability and statistics will take me ages...idk how i overcome this phase...anyway thanks for listening to my rant lol...
 
shivajikobardan said:
wow.. you are doing what every students nowadays can only dream of doing...one issue with me is that i was good at math and stuffs. but problem is i have forgotten everything as i didn't make notes. and i am thinking how will i study these 30+ subjects? did this happened to you? i am near graduation and i have only studied my 7th semester properly(i.e i made hipster pdas). i studied other semester like every other student(i didn't make hipster pda short notes for later to revise and neither did i made any good notes)...so to learn machine learning you need to know good amount of math and probability. learning 4 engineering mathematics and 1 semester probability and statistics will take me ages...idk how i overcome this phase...anyway thanks for listening to my rant lol...
Ha, thank you. I have a masters degree in statistics and had no experience with machine learning or modeling when I graduated. I think that the state of modern ML is it's good to understand data, stats, and programming to an intermediate level. After that it's all about gaining practical experience with real projects. There are so many Python libraries now that make ML very accessible. The problem is that it's almost too easy to where if you don't know the theory behind it at all, you won't notice mistakes. So again I think having a solid math/stats background assists but getting a job is about being able to code and finish real projects.

Have you explored fastai at all? I really like this free course because it comes with Python notebooks that open up in Google Colab. You can run the code and see how it works for real.
 

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