Choosing a Project: My Criteria and Friends' Examples

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SUMMARY

The discussion centers on selecting a suitable project for a group with limited programming experience, specifically in Django and Python. Participants emphasize the importance of choosing a project that is challenging yet manageable within a 1.5-month timeframe. They highlight the decision to pursue an employee promotion prediction project utilizing machine learning, acknowledging the necessity of a solid foundation in mathematics and statistics. Additionally, resources like fastai are recommended for practical learning through hands-on experience with Python notebooks.

PREREQUISITES
  • Basic knowledge of Python programming
  • Familiarity with Django framework
  • Understanding of machine learning concepts
  • Foundational knowledge in statistics and probability
NEXT STEPS
  • Explore fastai for practical machine learning applications
  • Study Python libraries for machine learning, such as scikit-learn and TensorFlow
  • Learn about data mining techniques relevant to employee promotion prediction
  • Review mathematical concepts essential for machine learning, focusing on statistics and probability
USEFUL FOR

Students and early-career professionals in programming, particularly those interested in machine learning and project-based learning. This discussion is beneficial for individuals seeking guidance on project selection and practical resources for skill development.

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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