Greetings fellow developers. I will complete MLS course 1 by the end of this week. Based on my learnings (Linear regression and Logistic regression) , Please suggest 3 ML projects based on increasing difficulty level. Also, is it too soon to get my hands dirty , given course 1 only includes training, not validating and evaluating ? Thanks in advance!
Hi @neevarp78,
It is never too early to get your hands dirty with real-world projects. Even if you haven’t formally covered validation and evaluation yet, working on projects will help you develop intuition about how models behave.
It’s difficult to give a universal recommendation like “pick dataset A and solve problem B,” because the best projects depend on your interests. That said, a general recommendation is to start with simpler regression and classification tasks that align with what you’ve learned so far.
Kaggle has a lot of datasets you can use.
You can also get free labeled datasets from online sources, such as the “UCI Machine Learning Repository”.
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