Earlier quoted context omitted.
Depends on the scope of the project. Would the goal be to come up with a better algorithm for cell classification based on histological images? Or to apply an existing algorithm to a new dataset? The former would be quite difficult without much background in ML/Computer Vision (you would have to spend some time self-teaching basics of ML/Deep Learning and the pre-reqs for those — Basic Linear Algebra and Probability)…
The data in the database comes from a bidimensional matrix (LMNE) where leucocytes are classified on resistivity on one axis and light absorption (?) on the other. (I wonder how they managed the separation by absorption... indirectly via centrifugation ?) So I guess not really histological ? Looks like it's a new model, I have no idea if they already have any ML models yet. There's also some database work. I'm finish…
Also, might be useful to took at webpages of some researchers in this space and courses they teach [1,2].
[0] https://web.stanford.edu/~hastie/ElemStatLearn/
[1] https://scholars.duke.edu/person/dunson
[2] https://www.cs.princeton.edu/~bee/