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Mastering Machine Learning in One Day
Get Free Ebook Mastering Machine Learning in One Day
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From the Author
Do you want to discover, learn and understand the methods and techniques of Artificial Intelligence, Data Science, Computer Science, Machine Learning, Deep Learning or statistics?If the answer is yes, you are in the right place. The AI Sciences book series is perfectly suited to your expectations!Our books are the best on the market for beginners, newcomers, students and anyone who wants to learn more about these subjects without going into too much theoretical and mathematical detail.About UsWe are a group of experts, PhD students and young practitioners of Artificial Intelligence, Computer Science, Machine Learning and Statistics. Some of uswork in big companies like Google, Facebook, Microsoft, KPMG, BCG andMazars.We decided to produce a series of books mainly dedicated to beginners and newcomers on the techniques and methods of Artificial Intelligence, Data Science, Machine Learning and Statistics. Initially, our objective was to help only those who wish to understand these techniques more easily andto be able to start without too much theory and without a long reading. Today we also publish more complete books on some topics for a wider audience.About our BooksOur books have had phenomenal success and they are today among the best sellers onAmazon. Our books have helped many people to progress and especially tounderstand these techniques, which are sometimes considered to be complicatedrightly or wrongly.The books we produce are short, very pleasant toread. These books focus on the essentials so that beginners can quicklyunderstand and practice effectively. You will never regret having chosen one ofour books.Wealso offer you completely free books onour website: Visit our site and subscribe in our Email-List.To Contact Us:aisciences.net
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Product details
Paperback: 185 pages
Publisher: AI Sciences LLC (March 20, 2019)
Language: English
ISBN-10: 1733570683
ISBN-13: 978-1733570688
Product Dimensions:
6 x 0.4 x 9 inches
Shipping Weight: 12 ounces (View shipping rates and policies)
Average Customer Review:
4.4 out of 5 stars
8 customer reviews
Amazon Best Sellers Rank:
#304,411 in Books (See Top 100 in Books)
A very well written book that takes you beyond the curiosity phase of your machine learning education. You need this book if you want to learn more about things like where and when apply this or that Machine Learning techniques.I respect where the authors are coming from, as they are trying to reduce his obvious experience in ML down helping readers to understand very clearly all the concepts. I believe they have accomplished this goal very admirably. Their easy style of writing encourages you to follow all the concepts and elements. This book will likely work for readers who only need to understand the theory behind Machine Learning! Take it and enjoy......
If English is these authors' native tongue, my name is Venkatanarasimha Rajuvaripet, which it is not. Nor am I from Mumbai, which is probably the hometown of these authors. The stilted writing and numerous grammatical errors render reading this book more challenging than necessary. The seven or so five-star reviews must be from their countrymen, who speak English a similar stilted and incorrect manner.
Wonderful
As a programmer, it's hard not to notice the tremendous excitement around and potential in Machine Learning and especially Artificial Intelligence these days. At the same time, for a complete newbie to the field, the space is so big it can be overwhelming to know where and how to get started. I just wanted to get a good vantage point on the field and an overview of the terms I'd seen bandied about.The book delivered, in spades. I like that it went over what it called the Machine Learning Algorithms and then gave a flavour of so many different kinds of other algorithms and use cases out there.My only one complaint is that it didn't present an introduction in Reinforcement Learning and deep learning at all. But it is okay because I need to master only supervised and unsupervised Learning techniques.
This book is a very convenient and a good survey of fundamental concepts (linear algebra, statistics and probability), different learning algorithms (Regression, Classification, Clustering and Associations) and practical considerations (data set, training and validation, outliers, missing data, best practices, overfitting and underfitting).The book is very nice and is consistent and coherent presentation of all of those ideas. The book is also packed with all the advantages and downsides about all the learning techniques and algorithms.As someone with an intermediate level of knowledge and experience of Machine Learning, I am grateful for this book, because it explains very clearly all the important concepts and elements.The book has excellent scope and depth, and I am confident that anyone will find this book to be very exciting and perhaps unique in its ability to take the reader to the next level. I was personally excited to learn about how to deal with missing data and outliers.Having said all of this, I think that everyone with beginner or intermediate level would benefit from this book. This book answers many of the questions that one is likely to have while learning Machine Learning fundamentals, and that's one of the book's tremendous values.I think this book is an excellent one in Machine Learning by AI Sciences, and I highly recommend it for gaining the solid background needed to have a thrilling experience with the Machine Learning practical books.In summary, I am very happy with the purchase of this book, and I think the book will be a great benefit to many beginner in the Machine Learning and AI Sciences field.
Machine Learning is the promising direction towards general purpose effective artificial intelligence. The book "Mastering Machine Learning " by AI Sciences is an excellent piece of work. They manage to present rather difficult things in an understandable manner. The theoretical presentation is outstanding typical of "classic" books. In addition, the book stays close to the practical applicability of all the methods and discusses advantages of each algorithm and how to deal with the data quality.There are a lot of other useful books on Machine learning that follow a more practical approach by focusing on a particular Machine learning software package, but this one book is certainly much more essential since it provides the required theoretical background in order to be able to do serious work on Machine learning.I consider the book as "must have" for anyone that works on Machine learning either in an academic or in an industrial environment.
First, I hesitated to buy this book so I visit the website aisciences.net, found some free books, and get a look at some of them. Their contents are great and I like it. After that, I came back to Amazon and purchase this book.This is one of the best books I bought at this price. That why I decided to write a review.This is a great book for breaking into machine learning or just looking up material. AI Sciences seem mastering very well Machine Learning, which allows them to recommend ways of approaching certain problems. Explain all the algorithms how they work, what is their advantage and downside.I like a much the Best Practice and dealing with Data Chapters. These two chapters give a very useful information for practitioners. The book explains typical ways of solving known problems, like dealing with data before taking the next step applying ML models. With the addition of some introduction to newer and less known concepts, this book kicks you in the right direction.If you're still unsure whether this book is worth the book; take it if you didn't like the content no problem you can ask for a refund and you will get your money back by Amazon !Hope that my review will help you then choose the right book in your Data Science journey.
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