These documents are part of a series of pages that are intended to be shared with the community of data science, machine learning, and artificial intelligence enthusiasts. It seems all to often to be the case that after courses are completed in university, that all the details of the material that were studied are quickly forgotten after the exams. For a group of people such as those previously mentioned, such a habit is counterproductive towards the work that we hope to do.
These are methodologies which we need to regularly implement at a fairly high level and so it is vital that we are able to easily access our notes on the topics so that a proper and thorough analysis can be completed.
Simultaneously, I understand that as a university student having studied in the U.S. that I am comparatively lucky compared to many around the world who lack access to such institutions with their wealth of resources. Another goal to be aimed for through the task of compiling these notes is to help increase the level of equity in the world by allowing others to improve their knowledge and thus raise the global standards for data science, machine learning, and artificial intelligence. This is something that has been greatly helped by pioneers such as Andrew Ng and his deeplearning.ai courses in combination with Coursera.
Disclaimer: It would make sense to interpret the work as a student’s set of notes rather than as authoritative educational texts.
