Today, machine learning underlies a range of applications we use every day, from product recommendations to voice recognition as well as some we don t yet use everyday, including driverless cars It is the basis of the new approach in computing where we do not write programs but collect data the idea is to learn the algorithms for the tasks automatically from data AsToday, machine learning underlies a range of applications we use every day, from product recommendations to voice recognition as well as some we don t yet use everyday, including driverless cars It is the basis of the new approach in computing where we do not write programs but collect data the idea is to learn the algorithms for the tasks automatically from data As computing devices grow ubiquitous, a larger part of our lives and work is recorded digitally, and as Big Data has gotten bigger, the theory of machine learning the foundation of efforts to process that data into knowledge has also advanced In this book, machine learning expert Ethem Alpaydin offers a concise overview of the subject for the general reader, describing its evolution, explaining important learning algorithms, and presenting example applications.Alpaydin offers an account of how digital technology advanced from number crunching mainframes to mobile devices, putting today s machine learning boom in context He describes the basics of machine learning and some applications the use of machine learning algorithms for pattern recognition artificial neural networks inspired by the human brain algorithms that learn associations between instances, with such applications as customer segmentation and learning recommendations and reinforcement learning, when an autonomous agent learns act so as to maximize reward and minimize penalty Alpaydin then considers some future directions for machine learning and the new field of data science, and discusses the ethical and legal implications for data privacy and security.
Machine Learning The New AI Today machine learning underlies a range of applications we use every day from product recommendations to voice recognition as well as some we don t yet use everyday including driverless cars It is
Recommended to me by a product manager at Hulu It s not too technical, but I wish the book was condensed into of a primer with theory conceptual discussion and examples rather than over explaining technical details The engineers reading will be sick of hearing it and the managers non engineers won t fully understand Overall, if you want to understand and introduction to machine learning and how it works, this book will do the job.
I listened to the audio book very passively The Machine Learning had a moderately sized emphasis on explaining various algorithms at which point I lost focus.This is probably a great primer, I believe, for students learning programming and artificial intelligence But for the lay person, this could be a difficult book to follow The upside, is that the book is currently very relevant, with its reference to Alpha Go , which is the artificial intelligence that beat one of the most complex board game [...]
I got this book in an audio format so thought it would be hard to understand with complicated formulas or algorithm, but it wasn t complicated at all It is about what is machine learning, how it evolved, or evolving, and what are some of the important topic of machine learning I think, this book is a great introduction to machine learning for people who do not have good mathematical or statistical background Of course, I didn t understand all the concepts mentioned, but whatever I understood, I [...]
I would highly recommend this book if you like to conceptually understand the different topics and models of Machine Learning as it exists today Ethem does a great job at explaining the big picture through common real life examples, using relatively standard math It s a great book for those who don t want to learn how to program Machine Learning but would rather understand how Machine Learning might influence design, strategy, and culture.
Just the perfect book to get a wide and shallow picture of all the topics concerned with data manipultation warehouse, mining, big data, machine learning, neuronal nets, statistics, regression analysis, distribution, clustering Really knew all this topics, but the book helped me arrange some concepts I had mixed up a bit
This gives a great overview of what Machine Learning is and where it is being applied The content is very current AlphaGo, Deep Learning, GANs, and also mentions the history of different ideas that make up machine learning today A good short read to get a non technical review of Machine Learning.
A great casual intro into the key concepts of AI and machine learning I had some solid product ideas after this, as well as some realizations that I wasn t thinking as deeply as I should Great summary I bought this at the gift shop at the Robots Exhibit at the London Science Museum.
A great overview of Machine Learning Not a deep dive into the mathematics or technical aspects of machine learning A great read nontheless.
Clearly written and clearly thought out, but shallow for anyone already familiar with the field.
Link to full version of book cs.du mitchell mario_book
Exactly what I was looking for an overview of the field that is technical but without a mathematical exposition More of a physical treatment.
Useless text don t waste your time.
The book great insights about what is machine learning, how are were using it, ways to enforce learning in machine and as a whole what impact it will create in our lives.
Was goed, maar te weinig diepgaand.
A very well done, non technical primer on machine learning.
Oscillates between being too simple and too complex.
Useful as a refresher and quick overview of the field, with pointers to the key papers for further in depth reading as needed.
Hardly qualify Essential Knowledge, better to read.
Very quick read I felt this was a good introduction to machine learning without being overly technical As someone who does not have a computer science background, there were certainly elements of the book that I didn t quite understand However, the author provided a good dose of real world examples that made the material accessible.
Fine A very liberal arts, high level explanation of machine learning techniques and broadly how they work Not super insightful and some of the explanations are so vague or vaguely worded as to not convey much information at all, but that s what happens when you re writing a non technical survey of a technical space.
2h 2.5x This quick conceptual introduction to machine learning felt, at different times, to both under overestimate the reader We somewhat know what computers are we want to understand what the algorithms do, and to learn about the implications like privacy prediction control that didn t get so much coverage But it s probably a tough balance to write pop ML, and this managed to present many main ideas very well on a conceptual level, including some history AI ML.The author has also written a tex [...]
A nice non technical overview on machine learning
A quick read that provides a great overview of where machine learning comes from and where it is going 4 stars.
Summary this book is for understanding the concepts of machine learning, not the doing, not the technology, and not the business it will drive That is, it explains the math and statistics at a conceptual level where anyone can follow.This book, oddly, starts by explaining the absolutely most trivial things about technology and the Internet e.g we now have smart phones But once that part has past, the author Alpaydin explains the conceptual ideas behind the algorithms and the thinking surrounding [...]
Computers were born rare big calculators evolving fast to a diverse, distributed and ubiquitous platform for general computation What a pace In parallel, all human endeavours are getting digital creating massive amounts of data In this book Ethem discuss how we are trying to teach computers to learn from such data The whole thing is structured in a timely manner together with its historic context Finishing strong with What the hell is Data Science Enlightening entertaining book.
An amazing book a great overview of the scope of machine learning algorithms as well as the kinds of applications that they have I was particularly impressed at how outdated MCMC techniques are, and how some techniques up to 2016 were referenced I really need to read books like these I thought the first couple of chapters were unnecessary though It didn t fit the pace or tone of the overall book.
Great intro to machine learning Good examples, and fairly accessible writing.It helped to have a strong background in statistics.The detours into social and ethical issues around machine learning were the weak spots in the book but for a basic overview of what machine learning is and what it can do this is a very good book.
Good introduction to the subject, but it touches a lot of concepts that seem difficult to grasp without a mathematics or computing science background and at the same does not seem to want to dig in the technical details It gives a strange mix On the bright side, this is a short read and an idea provoking book.
A decent high level overview of machine learning, for non technical types No math or code, but manages to convey the basic ideas behind fundamental ML algorithms from linear regressions to neural networks I listened to this as an audiobook
Nice conceptual overview of machine learning It doesn t teach you how to create but rather the major concepts