Karens already don't care when people tell them off. But what is it used for? Can you use facemask detection in shops? No. Not a great look.įacemask detection may seem like a great project in times of covid. The Iris dataset is already on a "too simple" list but also was collected by a eugenicist. But if your interviewers are ethically conscious, you may be in hot water with certain projects. There are many projects that sound interesting at first. Remember, in the first pass, recruiters will often only negatively filter and find reasons to discard your CV rather than giving you a chance. You can mention this capstone in the course work, but normally passing this off as project experience can negatively impact the evaluation of your CV during screening. You used to, but it won't do anymore, because everyone has taken that course by this point. In the same vein of simple projects, you will not be able to pass off capstone projects from Andrew Ng's machine learning course as project work anymore. There the focus is obviously on the novel application rather than solving MNIST.īasically, if it's a Kaggle playground project it doesn't belong on your CV. Santiago Valdarrama for example used MNIST to showcase contrastive learning on computer vision problems. If you demonstrate a novel approach to a problem on one of these data sets this may be an exception to this advice. However, these problems are also considered solved for the most part and don't showcase your skills adequately. They are natural learning points and in fact. I started my machine learning journey by building a neural network from scratch to predict MNIST. These are very good projects to get started. Many try out the Titanic dataset, build a small neural network to predict MNIST, dabble in the wine prediction dataset, or predict house prices in Boston. It is a way to show that you can learn new skills, and it is a way to show your ability to work in a team. The project is also a good way to show how you learn and how you work. So, when you go interview with the company, you can point to that project as a way of showing that you can do the work that they need done. As an example, you might have a data science project that focuses on building a machine learning model from a dataset. The projects should showcase your ability to do the work that the company needs done. If you are looking to get hired at a top company, you need to be able to point to a portfolio of projects that you have done. So you should definitely not underestimate the importance of project experience. This is because they want to know that you can do something with the data that you learned about in school. In my experience, most of the companies are looking for people who have some kind of project experience. But there is another aspect that is often forgotten: project experience. Most of these advices are about how you should learn more and more and more about data science, which is very true, by the way. The internet is filled with advice on how to get a job in data science.
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