How to start looking for machine learning opportunities in projects I am a software engineer who has taken an interest in machine learning about a year ago. I work on a couple of projects where a large amount of data is collected, and am wondering what I can do (or practice) in order to start recognizing opportunities to implement machine learning. Until now, I've spent some time building various classifiers with tensorflow, caffe, etc. using pre-defined data sets for random things I've found online (whether it be photos, spreadshets, etc) - and I just want to be able to use it at work. What is the best way to start getting in the frame of mind where I start recognizing where I can apply it? I found this article: https://hbr.org/2017/10/how-to-spot-a-machine-learning-opportunity-even-if-you-arent-a-data-scientist but it didn't seem too helpful to me. If there are any other thoughts and/or resources online that you could point me to, that would be helpful. Thanks.
If you are trying to see whether machine learning can contribute to your work, first thing you ought to do is to see if any of the following tasks could help the business at hand. Machine learning tasks include the following:


Classification
Regression
Clustering
Density estimation
Dimensionality reduction