Learning From Data (https://amlbook.com) is a great introduction to ML from a more theoretical perspective. The language is easy to understand but the concepts that it deals with are very theoretical, a combination that is hard to find elsewhere.
For example nearly everyone understands how to apply multivariable logistic regression, in say Numpy, however a good grasp of underlying concepts such as confidence bounds for overfitting and and being able to use formal proofs to explain concepts such as VC Generalisation will both help you stand out and provide a good foundation that makes further learning much easier.
Just tried this at university and interestingly all fig functionality is blocked when using the university's wifi, probably due to the proxies they have in place, while hot-spotting from my phone over 4g seems to work fine.
edit:
after switching back to university wifi fig also worked fine, so it may be an issue with the wifi or there may be a need to refresh the network connection when trying to set everything up
For example nearly everyone understands how to apply multivariable logistic regression, in say Numpy, however a good grasp of underlying concepts such as confidence bounds for overfitting and and being able to use formal proofs to explain concepts such as VC Generalisation will both help you stand out and provide a good foundation that makes further learning much easier.