Machine Learning For Absolute Beginners: A Plain English Introduction: 3 (Learn AI & Python for Beginners)
Product ID: 54604352
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NOTICE: To buy the newest edition of this book, please search "Machine Learning Absolute Beginners Third Edition" on desertcart. The product page you are currently viewing is for the 2nd Edition of the book. Featured by Tableau as the first of "7 Books About Machine Learning for Beginners" Ready to crank up a virtual server and smash through petabytes of data? Want to add 'Machine Learning' to your LinkedIn profile? Well, hold on there... Before you embark on your epic journey, there are some theory and statistical principles to weave through first. But rather than spend $30-$50 USD on a dense long textbook, you may want to read this book first. As a clear and concise alternative to a textbook, this book provides a practical and high-level introduction to machine learning. Machine Learning for Absolute Beginners Second Edition has been written and designed for absolute beginners . This means plain-English explanations and no coding experience required. Where core algorithms are introduced, clear explanations and visual examples are added to make it easy and engaging to follow along at home. This major new edition features many topics not covered in the First Edition, including Cross Validation, Data Scrubbing and Ensemble Modeling. Please note that this book is not a sequel to the First Edition, but rather a restructured and revamped version of the First Edition. Readers of the First Edition should not feel compelled to purchase this Second Edition. Disclaimer: If you have passed the 'beginner' stage in your study of machine learning and are ready to tackle coding and deep learning, you would be well served with a long-format textbook. If, however, you are yet to reach that Lion King moment —as a fully grown Simba looking over the Pride Lands of Africa—then this is the book to gently hoist you up and offer you a clear lay of the land. In this step-by-step guide you will learn: • How to download free datasets • What tools and machine learning libraries you need • Data scrubbing techniques, including one-hot encoding , binning and dealing with missing data • Preparing data for analysis, including k -fold Validation • Regression analysis to create trend lines • Clustering , including k -Means Clustering to find new relationships • The basics of Neural Networks • Bias/Variance to improve your machine learning model • Decision Trees to decode classification • How to build your first Machine Learning Model to predict house values using Python Frequently Asked Questions Q: Do I need programming experience to complete this book? A: This book is designed for absolute beginners, so no programming experience is required. However, two of the later chapters introduce Python to demonstrate an actual machine learning model, so you will see programming language used in this book. Q: I have already purchased the First Edition of this book, should I purchase this Second Edition? A: As the majority of the topics from the First Edition are covered in the Second Edition, you may be better served reading a more advanced title on machine learning. Q: Can I get access to the Kindle version of this book? A: Yes. Under desertcart’s Matchbook program, the purchaser of this book can add the Kindle version of this title (valued at $3.99 USD) to their desertcart Kindle library at no cost. Q: Does this book include everything I need to become a machine learning expert? A: This book is designed for readers taking their first steps in machine learning and further learning will be required beyond this book to master machine learning. Review: Gripping (factual books aren't supposed to be) - could barely put it down - Very logically structured and with clear chapters which hang together (about 5-10 pages long). It covers the components/decisions to make in Machine learning, data preparation, the main algorithm methods, the development environment and making a model in python. Don't be put off by the python you can read 90% of the book not knowing anything about Python. Great value for money I do have a background in stats and algorithms so even though the language is clear some of the underlying concepts do take a bit of thinking about. A suggestion if you cannot take the algorithms on board is to get 20 pictures of dinosaurs and try putting them into 2 categories using each of the "unsupervised" algorithms that the author describes - for the supervised algorithms get 20 pictures of cats/dogs and correctly label half of them (the "training set") as "Cat" or "Dog" leaving the other half without labels (to use either as "test" data or "actual" data)... Review: Good introduction. - It’s a good primer for any beginner who is curious about the field. Rather than just being an overview of the topic it gives some basic practical knowledge to make a start with machine learning. Losing a star due to being a very poor print. Mine had part of another book printed half way though not sure how that would even happen!
| Best Sellers Rank | 679,609 in Books ( See Top 100 in Books ) 756 in Computer Information Systems 2,168 in Computing & Internet Programming 14,589 in School Education & Teaching |
| Customer Reviews | 4.3 out of 5 stars 1,552 Reviews |
J**D
Gripping (factual books aren't supposed to be) - could barely put it down
Very logically structured and with clear chapters which hang together (about 5-10 pages long). It covers the components/decisions to make in Machine learning, data preparation, the main algorithm methods, the development environment and making a model in python. Don't be put off by the python you can read 90% of the book not knowing anything about Python. Great value for money I do have a background in stats and algorithms so even though the language is clear some of the underlying concepts do take a bit of thinking about. A suggestion if you cannot take the algorithms on board is to get 20 pictures of dinosaurs and try putting them into 2 categories using each of the "unsupervised" algorithms that the author describes - for the supervised algorithms get 20 pictures of cats/dogs and correctly label half of them (the "training set") as "Cat" or "Dog" leaving the other half without labels (to use either as "test" data or "actual" data)...
S**N
Good introduction.
It’s a good primer for any beginner who is curious about the field. Rather than just being an overview of the topic it gives some basic practical knowledge to make a start with machine learning. Losing a star due to being a very poor print. Mine had part of another book printed half way though not sure how that would even happen!
M**E
Perfect overview for the beginner, book exactly as sold on the packaging
This little introduction to Machine Learning is a gem. It is for the absolute beginner as it explains in the title. But it acts as an extremely useful helicopter view of the subject, not in journalist style, but actually very true to the mathematics and methodologies underlying the techniques. The book also helps those thinking about a career in machine learning. They will get an overview of what it is about and what types of skills are required. For those with a deeper mathematical maturity, this book could also act as a good reference framework for all the different approaches and techniques covered. For example, to understand what reinforcement learning is (and why it is so difficult) or ensemble learning techniques. The real difference between standard regression and logistic regression. Traditional textbooks and monographs can become overburdened in the technical mathematics and make the reader lost in terms of where they are in the whole overall scheme of machine learning.
M**D
Review
The book is ok for review of basic AIML. I found the book bit more technical for beginners as opposed to focusing on the basics.
D**C
A valid introduction to machine learning
I think this book does a really good job at explaining all the basic concepts of machine learning. I had started a Matlab course on ML at work for personal development but to be honest I hadn't taken the time to get an overview of the basic concepts written in clear understandable language. This does the job quite nicely. Some comments say that you can get all the information online... you could make thag comment about any knowledge base these days but thus is a well structured plain english book on machine learning that a pure beginner can sink their teeth into.
T**N
It is what it says 'a plain English introduction'
I wanted to know where to start in learning computer programming, and I think this book is a good beginning for anybody with very little knowledge.
D**N
Excellent starter book for Machine learning
I was looking for a starter book , considering I had zero knowledge of ML. This is absolutely perfect. The 15 chapters are each roughly 8 to 10 pages and can easily be read with a coffee in about 20 to 25 minutes. After 3 days, I am 5 chapters in and already have some of the large concepts and have a very brief idea of some ot the current buzzwords in ML I'd fully recommend this book for people like me who are new to ML. Darren
H**R
Best on ramp into ML I have ever found
I have just finished reading this excellent introduction to the topic of Machine Learning. It has been a long time since I have read any book in a single four hour sitting, with my brain so alight with the possibilities implied by what I’m reading about.
H**L
Un libro excelente para principiantes
es un libro excelente para aquellos, como yo, que desean iniciar su aprendizaje sobre el machine learning, en caso me resulto bastante útil para comprender lo básico, lo recomiendo a todos aquellos que desean comenzar su aventura, investigación, aprendizaje sobre este tema.
K**S
Does what is says
As its title says, this is an introduction. A short, structured book useful for pure beginners in order to get a good grasp of data science, machine learning and the main algorithms. Obviously less useful for people with preexisting knowledge in machine learning. Prior basic knowledge of programming and mathematics is recommended.
D**L
Concepts are very well explained
I highly recommend this book for people who want to start with Machine learning. It is a great starting point's book to get into this world. Concepts are very we'll explained. I started to understand things I had not been able to understand with other books and YouTube videos. It is helping me a lot to understand the foundations and key concepts of Machine learning.
U**R
Great for beginners!
I bought this book for my wife and I have never seen her so happy! She rarely finishes an academic book, but this one felt so natural for her to get to the end of it. She had no knowledge of machine learning but a physics background. This book gives a great way of starting into this fascinating topic!
J**S
Great book - easy to follow
This is a great resource to help get started with machine learning. It is well laid out and has good examples
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