These books will help you learn machine learning

reading is learning and as you'll see in this video I've put together some of my favorite books that have helped me learn machine learning and but it's by all means not an exhaustive list right I've missed out plenty of things so if if you do watch the video and you think of me something leave a comment below so that someone else can benefit from it but otherwise my style of learning is code and concepts first right so I've listed the books in this video in order of approachability alright so I learned the code and concepts first and then fill in the gaps with math where needed alright now you know that let's get started number one machine learning for humans by beshal meny and Samir Sabri our machine learning is broad alright there's algorithms for this there's data for this there's different ways to manipulate data for this algorithm there's problems that you'll have collecting data etc etc we know this right there supervised learning unsupervised learning deep learning and there's all different ways to work about them but somehow Michelle and Samir have managed to Compal eight a beautiful collection of explanations on all of the main topics in machine learning right right from supervised learning unsupervised learning reinforcement learning deep learning neural networks it's in there all within 96 pages right on you can read this online for free I don't have a full PDF but I've read it on medium as a series and both the PDF article now why is it important well if you knew the machine learning as I said they'll introduce you conceptually to some of the main topics in machine learning but if you're already in machine learning if you're already a practitioner it will give you an idea of a way to communicate a complex topic in a way that people can understand right because even if you are the smartest person in the room if you can't communicate what you know how helpful is that knowledge to someone else number two python for data analysis by where's McKenney now this one I do have a physical copy of I well because it's worth it now most of my time as a machine learning engineer is spent manipulating data analyzing it and getting it ready for modeling and 99% of the time I do that with pandas rights are performing data analysis with Pandits and so what is this well this is Python firt for data analysis data wrangling with pandas numpy and ipython which is Jupiter notebooks now but the important thing is that it's the author is where's McKenney right who's one of the creators of pandas which is the library I'm most use for manipulating and wrangling data so if you want to get into data science or machine learning you have to know how to manipulate data and this book will show you how okay number three so once you've read Python for data analysis you've got comfortable wrangling data with pandas you'll probably want to model it how do you do that you may use machine learning algorithms to find patterns out of data and now I don't have a physical copy of this book but I do have it on the Kindle and you can't really even see it there so I'm not sure why I'm holding up the Kindle I just put a nice photo of it here it's hands on machine lining with scikit-learn and tensorflow by órale on quran and now i got it on the kindle right because I was reading it to and from work on the train I wanted something that I could read just just go and update myself on on the best best machine learning techniques while I was going to work to use them the best thing about this book is that it will give you hands-on work through problems aren't using scikit-learn and tensorflow or psychic learners also called SK loom which are two of the most useful machine learning libraries if not that - most used for machine learning libraries out there and that's really important though for me I learn best by by seeing someone else do something so having those examples seeing how they're done I can go okay this is how it's done for this problem and come across my own problem compare the two and then adjust where it's needed so if you should take this book write five in for data analysis the hands on machine learning book with scikit-learn intensive flow these two together made up 80% of the things that I would do on a day-to-day basis as a machine-learning engineer so they're definitely worth your time number for grokking deep learning by Andrew Trask now again I don't have a physical copy of this one because when I first encountered it it wasn't fully out yet so way back when when I was doing the deep learning nanodegree by Udacity Andrew Trask was one of the guest lecturers and he was talking about LS TMS I think or language modeling something like that I can't remember the exact topic but what I do remember is his way of explaining things was very akin to how I like to learn things so using analogies like hyper parameters are like knobs on an oven which you can adjust those sort of things right I really that's those those click in my brain and so when I heard that he was altering a book rocking deep learning I jumped on it alright so I bought it at the time there was only five chapters I remember sitting on my couch reading through them right step by step and now up until that point for neural networks I've only ever used frameworks right but Trask insisted that in order to understand them deeply it was best to code them from scratch using numpy and so I kind of disagree right because I found the frameworks easier again me avoiding the hard thing to do but I followed trusts Lee coding over from scratch from numpy and gained a much better understanding than I did without so if you prefer a ground-up learning approach for deep learning rocking deep learning by Andrew Trask is for you wildcard time now this one doesn't have an actual number because it's not fully out yet that's a beautiful thing about open source right is that people can release things as they're being built so you can you can get value from them straight away now this one is the mechanics of machine learning by Jeremy Howard and Terence path you can read it online for free but remember at the time of recording it's not fully done yet but reason being Jeremy Howard founder of fast AI I absorb all of his teachings to do with machine learning right I really I really aligned with his style of teaching so I know it's in good hands if it's got his name on and Terence Parr is a professor of computer science at the same University at where Jeremy teaches out and after briefly going through some of the chapters on the book it's an incredible resource to learn machine learning so check it out the mechanics of machine learning number five the hundred page machine learning book by Andre they're called now this one I do have a physical copy why because it's the start here and continue here of machine learning and something that you should have on your coffee table right so you can pick it up someone can ask you about machine learning ask the RO what's really going to take over and you can say no I've read this book and I know what machine learning actually is alright and so this is the book that I wish that I had when I started learning machine learning I probably wouldn't have got a lot of the concepts in here when I first started right because it is that little bit little bit advanced and even now into it two years there are some things that I don't understand but that's that's alright it's only a hundred or so pages you can read it in about a day I took longer than that I did make a full review video on this by the way so if you want more details on it check out there I'll put that in the description it covers end to end the broad spectrum of of the most useful things that you should know about machine learning and explains them in a simple easy-to-understand way now by sex now this is the last one but by all means again this is not an exhaustive list but I'm just sharing you some of my favorites the last one is deep learning by Iain Goodfellow yoshua bengio and erinkoval alright now if you haven't heard of in good fellow or yoshua bengio or on Courville you could pretty much say that they're they're some of the founding figures of deep learning as a whole and now when I first encountered this video this this this book two years ago it scared me right because you can read it again online for free but I started going through the pages and I read I read I saw the big paragraphs of text I saw the the equations and math equations and I'm like no I'm sticking to the code and concepts but then I realized in order for me to take it to the next level I need to I've kind of learned from a top-down approach remember but now I need to go back and fill in the gap from a bottom-up approach and now this is this is where this book is I plan on using this book for now I'm most excited for the for the chapters on math all right because in the end code frameworks languages etc will change but math stays the same over the long term and that's what I'm going for right I want knowledge over the long term my mistake in the beginning was being scared of books that were too hard for me when really in order to keep learning I have to remind myself Daniel you should be reading at all times a book that is slightly too hard for you to read because why eventually that book won't be too hard for you for to read and then you find another one that's slightly too hard to read so with that I hope you check out at least one of these books or or if not more there'll be there'll be links for all of them in the description so you can check them out there I hope they bring you as much value as they brought me and remember I have $30 or whatever the price of a book is or even free for some of them even if they give you one concept that you use for a number of years that's money well spent if you have any other books that you think I've missed leave a comment below so that others can see and so so I can see as well otherwise keep learning remember learning is reading so keep reading and keep creating we'll see you next time

Channel: Daniel Bourke

Views: 118,187

Rating: 4.9718575 out of 5

Keywords: the best books for machine learning, best books to learn machine learning, what are the best books to learn machine learning?, machine learning books, machine learning engineer, daniel bourke, best books for learning machine learning 2019, best machine learning books 2019, machine learning, books for machine learning

Id: 7R08MPXxiFQ

Length: 10min 22sec (622 seconds)

Published: Sun Aug 18 2019