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Editorial Reviews
About the Author
Reviews:
5.0 out of 5 stars an excellent non-technical overview of data science
Data science is put in excellent perspective in this book. I think the book is especially oriented toward giving people interested in "specializing" in this field or utilizing data science some good, basic information. As a multidisciplinary field, and one oriented toward business, government and surveillance interests, generally, it is a field that encompasses and extends into practical areas that its associated traditional area, namely statistics, has not in the past much-addressed. Data science is an extremely interesting, technical field with broad social and ethical implications explored in this book. Statistics is only one tool. The authors lucidly discuss the focus on the huge amounts of valuable, unstructured data. They point out that to make all of this useful for the goals and purposes of business, surveillance, medicine, government, etc. requires an enormous time investment in putting appropriate data together and extracting information in a usable form. The discussion of mathematical modeling, machine learning, and the overall use of algorithms is very insightful. The authors make it clear that data science is not merely "deep learning", despite the fact that the extraordinary advances in using neural nets represented by deep learning is largely responsible for much of the importance of data science today. There are excellent perspectives of data science available on the Internet, but I think the authors of this book have provided a good supplement for this information in a deeper way. One of the real problems in picking information out from the Internet is escaping the "hype" surrounding a subject that is currently "hot" like data science. This book definitely allows the interested person to separate some of the solid pieces of knowledge about what the field involves from the huge amount of "noise" surrounding the entire area of "weak" AI and machine learning. I would recommend this book strongly to anyone seriously considering going into this field. A point the authors stress is that weak AI, namely specialized applications, rather than broadly "intelligent" systems competitive with general human intelligence, has opened up a world of opportunity, promise, progress, as well as ethical dilemmas. I personally think that data science is a great field for an enormous spectrum of technicians at all educational levels. The book opens a window a bit on the enormous implications for our future. It is a good start on the climb to a satisfactory knowledge of this field and its potential. I especially recommend the book to business executives and entrepreneurs as a useful and insightful view, for developing a strategic picture of this field, that does not get into unnecessarily technical details, and is not subject to the "hype" and "noise" from the Internet.
4.0 out of 5 stars good data science primer
This book covers core concepts in data science in an easy to read manner. Infrastructure for handling big data and the data science ecosystem are introduced along with Machine Learning basics and some useful concepts at a high level(like CRISP-DM, clustering, anomaly detection etc.). A chapter on the privacy and ethics covers GDPR and biases in algorithms. Overall, a good general introduction.
5.0 out of 5 stars An excellent intro into Data Science
The authors do an excellent job of giving a very high level overview of the following for Data Science:-History-Applications (Prediction, clustering, anomaly detection)-Tools of Data Science (Bayes Rule, Logistic Regression, Neural Networks, Decision Trees)-Ethical concerns (Where do we cross the line between privacy, security and applications of the Data Science?)-Growth of Data Science (I wish the authors would've shared how to get into the career field more. Since applying association rule here, anyone that reads the book is likely to be interested in Data Science).
5.0 out of 5 stars Must-read for anyone who wishes to enter data science
Well-written and easy-to-understand, this book gives a new-comer like me a conceptual framework to think about problems in data science. It helps me to understand what the field really is and what the workflow of a data science project looks like. Particularly interesting is the chapter on data ethics and regulation. I think it is an area that is often overlooked by technical textbook, but should really be emphasized to readers who might someday become a data practitioner. Overall, it’s a very good book and worths your effort to delve into.
3.0 out of 5 stars Only the last chapter was original content
The last chapter was really good. wish authors provided more insights into successful data science projects. The rest of the book was very generic information.
5.0 out of 5 stars Good for use as course material
Good introductory book for data science. Use it for a lot of my college courses for the last couple years.
4.0 out of 5 stars Really good coverage and introduction to the big topic of data science
Easy to read with accessible and clear examples throughout. Well organised with an easy to follow structure throughout which is well tied together at the end
5.0 out of 5 stars Excellent book to get an overall picture
I am a relatively experienced programmer and have been involved in all parts of Data Science projects (ranging from leading big data processing parts to being an observant in ML parts also actively working with business to understand problems, justify investments and calculate ROIs for multiple proposed ML solutions) and come from a mostly practical background. This book provided a very good overall picture as well as a lot of good references to dig further into.
Good introduction to data science
This is an easy-to-read guide to data science. I think it covers the subject quite widely and is accessible to the general reader.Even though I have studied data science through online courses and other books, I still found things of interest in this book.What I found to be most interesting was the explanation of the CRISP-DM methodology which seems to be absent from the other data science sources I had been exposed to.If you want to explore data science, start with this book before moving onto books by Cathy O'Neill, or courses on Coursera or Edx.
O livro nos apresenta uma ideia geral sobre Data Science
Os autores se propuseram a apresentar e discutir os fundamentos da ciência de dados.Para tanto, ao longo do texto aprsentam as principais definições da área, além de discutirem a questão da privacidade dos dados e ética na aquisição/uso dos dados.
Claro y sencillo
Completo y claro
Explica bien los detalles del tema.
Buen libro. Directo al tema desde los primeros capítulos. Bien explicados. Intro que te sirve para entender más el tema y entrar a detalle luego de conocer el panorama completo
A map of Data Science
A small book covering essentials of the subject. Absolutely must for amateurs and beginners of Data Science.
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Data Science (The MIT Press Essential Knowledge series)
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Visit the The MIT Press Store
Data Science (The MIT Press Essential Knowledge series)
AED7208
Quantity:
Order today to get by 7-14 business days
Delivery fee of AED 20. Free for orders above AED 200.
Imported From: United States
At BOLO, we work hard to ensure the products you receive are new, genuine, and sourced from reputable suppliers.
BOLO is not an authorized or official retailer for most brands, nor are we affiliated with manufacturers unless specifically stated on a product page. Instead, we source verified sellers, authorized distributors or directly from the manufacturer.
Each product undergoes thorough inspection and verification at our consolidation and fulfilment centers to ensure it meets our strict authenticity and quality standards before being shipped and delivered to you.
If you ever have concerns regarding the authenticity of a product purchased from us, please contact Bolo Support. We will review your inquiry promptly and, if necessary, provide documentation verifying authenticity or offer a suitable resolution.
Your trust is our top priority, and we are committed to maintaining transparency and integrity in every transaction.
All product information, images, descriptions, and reviews originate from the manufacturer or from trusted sellers overseas. BOLO is not affiliated with, endorsed by, or an authorized retailer for most brands listed on our website unless stated otherwise.
While we strive to display accurate information, variations in packaging, labeling, instructions, or formulation may occasionally occur due to regional differences or supplier updates. For detailed or manufacturer-specific information, please contact the brand directly or reach out to BOLO Support for assistance.
Unless otherwise stated, all prices displayed on the product page include applicable taxes and import duties.
BOLO operates in accordance with the laws and regulations of United Arab Emirates. Any items found to be restricted or prohibited for sale within the UAE will be cancelled prior to shipment. We take proactive measures to ensure that only products permitted for sale in United Arab Emirates are listed on our website.
All items are shipped by air, and any products classified as “Dangerous Goods (DG)” under IATA regulations will be removed from the order and cancelled.
All orders are processed manually, and we make every effort to process them promptly once confirmed. Products cancelled due to the above reasons will be permanently removed from listings across the website.
Description:
Editorial Reviews
About the Author
Reviews:
5.0 out of 5 stars an excellent non-technical overview of data science
Data science is put in excellent perspective in this book. I think the book is especially oriented toward giving people interested in "specializing" in this field or utilizing data science some good, basic information. As a multidisciplinary field, and one oriented toward business, government and surveillance interests, generally, it is a field that encompasses and extends into practical areas that its associated traditional area, namely statistics, has not in the past much-addressed. Data science is an extremely interesting, technical field with broad social and ethical implications explored in this book. Statistics is only one tool. The authors lucidly discuss the focus on the huge amounts of valuable, unstructured data. They point out that to make all of this useful for the goals and purposes of business, surveillance, medicine, government, etc. requires an enormous time investment in putting appropriate data together and extracting information in a usable form. The discussion of mathematical modeling, machine learning, and the overall use of algorithms is very insightful. The authors make it clear that data science is not merely "deep learning", despite the fact that the extraordinary advances in using neural nets represented by deep learning is largely responsible for much of the importance of data science today. There are excellent perspectives of data science available on the Internet, but I think the authors of this book have provided a good supplement for this information in a deeper way. One of the real problems in picking information out from the Internet is escaping the "hype" surrounding a subject that is currently "hot" like data science. This book definitely allows the interested person to separate some of the solid pieces of knowledge about what the field involves from the huge amount of "noise" surrounding the entire area of "weak" AI and machine learning. I would recommend this book strongly to anyone seriously considering going into this field. A point the authors stress is that weak AI, namely specialized applications, rather than broadly "intelligent" systems competitive with general human intelligence, has opened up a world of opportunity, promise, progress, as well as ethical dilemmas. I personally think that data science is a great field for an enormous spectrum of technicians at all educational levels. The book opens a window a bit on the enormous implications for our future. It is a good start on the climb to a satisfactory knowledge of this field and its potential. I especially recommend the book to business executives and entrepreneurs as a useful and insightful view, for developing a strategic picture of this field, that does not get into unnecessarily technical details, and is not subject to the "hype" and "noise" from the Internet.
4.0 out of 5 stars good data science primer
This book covers core concepts in data science in an easy to read manner. Infrastructure for handling big data and the data science ecosystem are introduced along with Machine Learning basics and some useful concepts at a high level(like CRISP-DM, clustering, anomaly detection etc.). A chapter on the privacy and ethics covers GDPR and biases in algorithms. Overall, a good general introduction.
5.0 out of 5 stars An excellent intro into Data Science
The authors do an excellent job of giving a very high level overview of the following for Data Science:-History-Applications (Prediction, clustering, anomaly detection)-Tools of Data Science (Bayes Rule, Logistic Regression, Neural Networks, Decision Trees)-Ethical concerns (Where do we cross the line between privacy, security and applications of the Data Science?)-Growth of Data Science (I wish the authors would've shared how to get into the career field more. Since applying association rule here, anyone that reads the book is likely to be interested in Data Science).
5.0 out of 5 stars Must-read for anyone who wishes to enter data science
Well-written and easy-to-understand, this book gives a new-comer like me a conceptual framework to think about problems in data science. It helps me to understand what the field really is and what the workflow of a data science project looks like. Particularly interesting is the chapter on data ethics and regulation. I think it is an area that is often overlooked by technical textbook, but should really be emphasized to readers who might someday become a data practitioner. Overall, it’s a very good book and worths your effort to delve into.
3.0 out of 5 stars Only the last chapter was original content
The last chapter was really good. wish authors provided more insights into successful data science projects. The rest of the book was very generic information.
5.0 out of 5 stars Good for use as course material
Good introductory book for data science. Use it for a lot of my college courses for the last couple years.
4.0 out of 5 stars Really good coverage and introduction to the big topic of data science
Easy to read with accessible and clear examples throughout. Well organised with an easy to follow structure throughout which is well tied together at the end
5.0 out of 5 stars Excellent book to get an overall picture
I am a relatively experienced programmer and have been involved in all parts of Data Science projects (ranging from leading big data processing parts to being an observant in ML parts also actively working with business to understand problems, justify investments and calculate ROIs for multiple proposed ML solutions) and come from a mostly practical background. This book provided a very good overall picture as well as a lot of good references to dig further into.
Good introduction to data science
This is an easy-to-read guide to data science. I think it covers the subject quite widely and is accessible to the general reader.Even though I have studied data science through online courses and other books, I still found things of interest in this book.What I found to be most interesting was the explanation of the CRISP-DM methodology which seems to be absent from the other data science sources I had been exposed to.If you want to explore data science, start with this book before moving onto books by Cathy O'Neill, or courses on Coursera or Edx.
O livro nos apresenta uma ideia geral sobre Data Science
Os autores se propuseram a apresentar e discutir os fundamentos da ciência de dados.Para tanto, ao longo do texto aprsentam as principais definições da área, além de discutirem a questão da privacidade dos dados e ética na aquisição/uso dos dados.
Claro y sencillo
Completo y claro
Explica bien los detalles del tema.
Buen libro. Directo al tema desde los primeros capítulos. Bien explicados. Intro que te sirve para entender más el tema y entrar a detalle luego de conocer el panorama completo
A map of Data Science
A small book covering essentials of the subject. Absolutely must for amateurs and beginners of Data Science.
Similar suggestions by Bolo
More from this brand
Similar items from “Data Processing”
Share with
Or share with link
https://www.bolo.ae/products/U0262535432