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    KDnuggets 500彩票下载app二维码 » News » 2020 » Jan » Tutorials, Overviews » The Book to Start You on Machine Learning ( 20:n02 )

    Silver BlogThe Book to Start You on Machine Learning


    This book is thought for beginners in Machine Learning, that are looking for a practical approach to learning by building projects and studying the different Machine Learning algorithms within a specific context.

    By , Universidad Politecnica de Madrid


    Cover of the Book.


    A question a lot of ML practitioners get asked a frequently is: “What can I do to start being able to actually build Machine Learning projects and solutions?”

    There is so much information out there — both good and bad — that it can be hard to know where to begin. Also, people come from very different backgrounds, so the starting point can vary significantly. For example, for me, I entered the ML world by watching theoretical videos from Computer Science channels about neural networks, and as I got more and more interested I started reading articles, news, and blogs about the topic.

    However, by doing this I only developed a vague understanding of the most superficial part of Machine Learning, and I was nowhere near being able to tackle a project by myself. Knowing this I decided to take some affordable . Courses like these were helpful, as they rounded and improved my knowledge a little bit, and also covered some Python implementations of different algorithms and models.

    Still, the courses did not leave me content with what a knew, and I wanted to go deeper, understand every conversation, know the guts of the algorithms, and develop and understanding of how to build an End-to-End Machine Learning project by myself. I wanted to be able to have and idea, build or download a data-set, and execute it.

    And this is where the book that I am going to talk about comes in.

    — Heads up: This article contains Affiliate links so that you500彩票下载app二维码 can comfortably buy any of the books without any extra charge while contributing to the creation of more posts like this one —

    I read this book a while ago, but with the publication of it’s new edition I thought it would be a good idea to share my thoughts about it.


    Old edition of the Book.


    This book is “. It is a book that was originally published in 2017 and that still, in my opinion which each new revision has become an even better version of one of the best in-depth resources to learn Machine Learning by doing.


    Who is this book for?

    This book is thought for beginners in Machine Learning, that are looking for a practical approach to learning by building projects and studying the different Machine Learning algorithms within a specific context. After completing the whole book you500彩票下载app二维码 should be ready to face a project by you500彩票下载app二维码rself and be confortable with the different steps in this process.

    Despite being an fairly initiative book, it will also add some tools to the tool-kit of a medium-level Machine Learning practitioner.

    The book assumes you500彩票下载app二维码 have certain programming experience in Python, and know how to use the main scientific libraries: Numpy, Pandas,and Matplotlib.

    Also, if you500彩票下载app二维码 want to get the most out of it, it is advisable to have some basic maths, algebra and statistics knowledge. Apart from this, you500彩票下载app二维码 can finish it easily with very little or no initial understanding or Machine Learning if you500彩票下载app二维码 are willing to make an effort.

    Everything is very clearly explained, with code snippets, notes, and examples.


    What does it include?

    As I mentioned earlier, this is a very practical book that already on Chapter II gets you500彩票下载app二维码 working and coding a project. Before that, it describes what Machine Learning is, what it is not, its fundamentals, and its main applications and strengths.

    It shows how to implement the different Machine Learning algorithms, and covers the theory about them that you500彩票下载app二维码 to know, without extensively going into it and torturing you500彩票下载app二维码 with millions of complicated equations. The newest edition is composed of 19 chapters, which are divided into two blocks:

    • Part I, where the main concepts of Classification, Regression, Dimensionality Reduction, and Unsupervised Learning techniques are explained, along with traditional Machine Learning algorithms like Linear Regression, Logistic Regression, Support Vector Machines, Decision Trees or ensemble models.
    • Part II, which is focused on Artificial Neural Networks and Deep Learning using Tensorflow and Keras. Convolutional Neural Networks and Recurrent Neural Networks are explained, along with Auto-encoders and there is even a chapter on Reinforcement Learning.

    Each chapter is further divided into a more granular structure that takes us through it step by step, and the book also contains various Appendixes.

    The Chapters are the following:

    • Part I: 1. The Machine Learning landscape, 2. End-to-End Machine Learning project, 3. Classification, 4. Training Models, 5. Support Vector Machines, 6. Decision Trees, 7. Ensemble Learning and Random Forest, 8. Dimensionality Reduction, 9. Unsupervised Learning Techniques.
    • Part II: 10. Introduction to Artificial Neural Networks with Keras, 11. Training Deep Neural Networks, 12. Custom Models and Training with Tensorflow, 13. Loading and Preprocessing Data with Tensorflow, 14. Deep Computer Vision Using Convolutional Neural Networks, 15. Processing Sequences Using RNNs and CNNs, 16. Natural Language Processing using RNNs and Attention, 17. Representation Learning and Generative Learning Using Autoencoders and GANs, 18. Reinforcement Learning, 19. Training and Deploying Tensorflow Models at Scale.

    As I mentioned earlier, in each chapter we find code snippets and side-notes to complement the explanation along with figures, images and graphs, and at the end of each individual chapter there is a set of questions and exercises that are solved in one of the Appendixes.

    Also, a very useful addition to all of this is a Checklist for what to do step by step in a common Machine Learning project.


    How to read this book?

    Every person is different, but for me what worked best was to read the book on paper while writing notes on the side. Simultaneously I would try to go through the code, and every time at the end of the chapter I would take my time to answer the questions and do the mini — exercises. If I got stuck or I didn’t know how to do something I re-read some parts of the chapter or looked for information on-line.


    What Impact will this book have on me?

    If you500彩票下载app二维码’ve just started studying Machine Learning, this book will take the theoretical knowledge you500彩票下载app二维码 have, considerably improve it, and then put it to use in some real projects. Many times we are not able to test how much we know about something until we try to put it in practice. By reading this book you500彩票下载app二维码 will be completely ready to work in projects of you500彩票下载app二维码r interest.

    If you500彩票下载app二维码 already know about Machine Learning and have worked on some projects, this book will round up you500彩票下载app二维码r theoretical knowledge, teach you500彩票下载app二维码 some practical tricks that you500彩票下载app二维码 probably ignore, and advise you500彩票下载app二维码 on how to structure you500彩票下载app二维码r projects in an optimal manner. It is a wonderful book to have near-by to answer specific questions that might arise in you500彩票下载app二维码r day to day work.


    What to do next?

    After you500彩票下载app二维码 have finished this book I would encourage you500彩票下载app二维码 to think of a couple of projects you500彩票下载app二维码 would like to do with Machine Learning and with the book by you500彩票下载app二维码r side, try to execute them. This will test you500彩票下载app二维码 on real world problems, make you500彩票下载app二维码 face some of the difficulties of Machine Learning projects, and also you500彩票下载app二维码 will be building a portfolio of solved problems that will be of high value in you500彩票下载app二维码r learning and in you500彩票下载app二维码r future as a Machine Learning engineer or Data Scientist.


    Other Machine Learning books from my library


    Once you500彩票下载app二维码 feel confortable tackling these kind of projects, if you500彩票下载app二维码 want to go even further and come closer to an expert, you500彩票下载app二维码 could try the same procedure you500彩票下载app二维码 did with this book but with a more advanced one, like one of the following:

    Or if you500彩票下载app二维码 are interested in less technical books and want to explore the curiosities, dangers, and reach of Artificial Intelligence, you500彩票下载app二维码 could read one of the books described in:

    Three incredible AI books to make you500彩票下载app二维码r mind wander and you500彩票下载app二维码r thinking flourish.

    Also, if there is a specific area of Machine Learning which you500彩票下载app二维码 want to specialise you500彩票下载app二维码rself in, you500彩票下载app二维码 could look for a book on that topic, or even a more specialised online course.


    Closing words

    As always, I hope you500彩票下载app二维码 enjoyed the post, and that I have convinced you500彩票下载app二维码 to read the book.
    Here you500彩票下载app二维码 can find the link to the newest edition:

    If you500彩票下载app二维码 liked this post then feel free to follow me on . Also, you500彩票下载app二维码 can take a look at my other posts on Data Science and Machine Learning . Have a good read!

    If you500彩票下载app二维码 want to learn more about Machine Learning and Artificial Intelligence follow me on Medium, and stay tuned for my next posts!

    Until then, take care, and enjoy AI!

    Bio: is an Industrial Engineer with a bachelor specialized in Electronics and a Masters degree specialized in Computer Science.

    . Reposted with permission.


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