Book Review: Pattern Recognition and Machine Learning

Christopher Bishop

Month of January begun with this amazing book, so far things about this
* Language is not apt for people with no background in statistics and higher mathematics.
* Content is a little overwhelming for a beginner

Now reasons I like it
* Course structure is most logical to follow
* Maths is a little tough, but for now paying attention to backend math is of little importance if the concept is well understood, be it from applicability point of view, or even diagramatically
* Complexity can be postponed but not avoided, so i am not thinking of absorbing everything all at once, rather going slow, just giving it a read, and slowly fix things to my brain

I have tried various ways to conquer the coursework of Data Science, beginning from figuring out right trajectory of steps to learn things from most easy to most difficult. Books I think are very useful to provide one binding set of rules to follow, else you just keep on wandering endlessly.

I have also parallely trying to replicate already solved bookwork thorough github repositories. Way to mount this track is to write about topics you study and make your own repository with hints of other sources.

Here is the link to pdf of book. I think additional help on the book like few takeaways from each chapter or like a shorthand revision notes would be useful, probably i will find some time to formulate that too along with learning it. Let me know if that would help.