Data science vs machine learning
I’m interested in changing roles within my company. I’m considering shifting to people leadership role in either machine learning or data science. While I am technical, my background is not in either of those fields. I have started taking some (introductory) online courses, but to date I have not been able to discern clear differences between the data science vs machine learning roles - they seem to be closely tied together. I’d like to get a better understanding of the differences between the roles.
Data science is about feature engineering and machine learning is about job scheduling.
Not sure I’d want to work for you. If you expect to lead either team, I advise you to put more serious effort into learning it.
@OP: let’s see if I can clarify my comment in a more constructive way. You’re going into a field where I assume most of the ppl you’re managing will have graduate degrees. That means we’ve put a ton of effort into mastering our profession. We realize this is a hot field that lots of ppl want to get into. For you to come in not knowing what you’re doing and lead us, that’s like asking a captain to steer a boat who doesn’t know how to sail. So learn how to sail. Then we’ll talk. @clhl04 it’s not worth responding to you. Have a nice day.
Y’all are harsh - I told you I am just starting I learn about it... trying to learn a lot more first.
I highly recommend textbooks over online courses. They don't nearly give you enough detail and challenging concepts. To manage a data science team, you should have more experience than them to know how to clear roadblocks and use your domain and technical expertise to educate them on new methods to handle oddities in industry specific data
Thank you - do you have specific textbooks you would recommend?
Principles of statistical learning I consider the intro Bible to data science. The focus also shouldn't be to build the most "cutting edge" models, because 1. They aren't worth the complexity vs interpretability trade-off and 2. The data that goes in matters 1000x more than the model you use
Technology has matured a lot...reality of the world is that most of the problems are being solved through simple regression analysis...only research area requires deep expertise. You may be successful if you push hard to figure out use cases where you can apply it and make a difference rather then the tech itself. As a manager you would always be more effective when you contribute and believe in your team for the tech piece
K that’s helpful. I prefer to hire well and trust my team to get the in the weeds details correct - that’s why I hire them, right? But I need to understand what they are doing at a deep enough level that I can steer the general direction of the team and understand the good/bad/ugly of the options they present to me and understand the recommendation or help them arrive at a recommendation.
Ymccg47 and Alpha Zero = poor colleagues. Support your peers when they are looking to grow - don’t stunt them. What you put out you get back. Remember that.
I absolutely support my colleague! I have been teaching people stuff since I joined this retarded company. The problem is that there are people up high who are clueless and are not competent enough to do their job. This guy at least wants to learn, but i bet that at work, he still bs pretending he knows stuff. If you want to learn, join as entry level in ml or ds..... don’t work as mgr or lead and bs. Skill should match level.
Yacm! Yet another clueless manager