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Useful reference for updating my thoughts on Data Analysis and analytics. I personally liked the examples through the book, but would recommend it converted into an audio book as the detail in the book was compiled in an almost conversational sense, or as a lecture series (in my mind). I can see this aimed at an organisation that is little and growing, or old school and could see the benefits of tapping into readily available externally available information.
Understand data and interpreting it is necessary to your business and this book explain that in an simple to understand manner, but I would like to see more detailed examples on how to collect the info and what tools to use if you wish to obtain the most of them. Anyway is a goodintroduction to the subject.
A short book but could summarize what we need to know about Data Science, Huge Data and especially Data is book does'nt teach us the detail things but give us a bird view of these topics. To a further need, the readers have to read other books but, at the beginning all people only need to read this ebook to grasp the main concepts at first.A useful book for me on the method of starting learning Data Analytics.
This short introduction is well written and provides the uninitiated an beginning foundation to build oupon. It provides definitions for the common terms and provides the reader with understandable examples of a relatively easy nature. while easy they are informative and present the possibilities of Huge Data and Data analytics.
Amazing book with a very clever our Hi-tech developing world, you need every time to analyse the data around you. If not, you will loose your money, your time. As a general rule, the most successful main in life is the man who has the best information - and this book can support you to be this man.
Not sure the title is accurate, this is a very introductory level view of the subject. It seems to be written in the style of someone speaking casually. I think a amazing proof reader could really benefit this book. The author seems very well intentioned however the content just falls a bit short. A harsh edit and some concrete info instead of contrived examples would go a long method in making this a more satisfying read.
This is a very comprehensive book which reveals the importance of Data Analytics in business: large volumes of info which is processed and analyzed with the goal of predicting patterns and improving the managerial decision-making process. After reading this book, you will definitely have a complete understanding of the concept.
This book has introduced a wide range of ideas and concepts used for deriving useful info from a set of data. And also it contains data analytics techniques and what can be achieved by using them. It includes huge data analysis, advantage, considerations of pros and cons, methods, and more. The importance of huge data is also showed in this book as well as the software and everything required to improve business data.
It's a broad high level overview of how data analytics can support businesses increase their productivity and gives guidance on the correct policies and tactics to adopt towards that end.
Data analysis is at least as much art as it is science. This book is focused on the info of data analysis that sometimes fall through the cracks in traditional statistics classes and textbooks. I concise introduction and instructions about all stages of data analysis. Each subject can be expanded into a much more deep communication but the suggestions mentioned are very practical. I think it's a amazing starting point if you're a new-comer to data analysis. And it would be helpful to frequently look it up when you're doing the process to create sure you're on the right track.
Data analytics is something that all businesses need but not most businesses have. My parents taught me this lingo as they own a successful coffee shop. They also said to educate yourself to create intelligent decisions and to avoid ignorance. With that being said I bought this book to solely educate myself in data analytics as I endeavor to continue my parents business. I found this book to be enlightening and jam-packed with information. My favorite subject covered in this book is data management. Amazing read so far and I will tell my parents about it
This is really an awesome resource that defines data analysis and tools and methods that create it successful. I really need to develop my data analysis so that I will not be left behind in the ground. This book is very informative and a very useful tutorial for beginners to easily understand data analytics. A very spoon fed knowledge to the readers wanting to understand and learn data analytics. Time is spent wisely with this book. My deepest gratitude to this book for sharing these ideas.
Amazing light brush type to what data analytics is and how it can support a business. l was really looking for something a small deeper with more detail. I like the method the author covered the terminology and the processes. This would be a amazing book for say an executive level person who has to interact with the data analytical function but is not involved in the day to day operations.
One of the few books on data analytics that I've read cover to cover. In looking over my kindle reader highlights...counted over 50 highlights over the entire book. Have referred back to those highlights when reading from other resources on data analytics.
Absolutely worthless. Not a book but a triple-spaced size 18 font glossary. You could read this entire book in less than 15 minutes, some kind of scam.
Very primary level information, an introduction to the topics. I bought the paperback ver and the formatting is poorly done. Seems slapped together for a paper release.
For me very useful in book chapter where author explain : social media tactics for the business owner. If you have own business please read this book you can search a lot of tips and tactics for increase your business. Its really special book with special info if you begin own business and YOU test develop YOUR business.
First time Amazon teaches me not to believe the reviews. This book has less content than even a web post. Just a few bullets with few comments. You're reading this book like reading someone's tweets. Returning it back, now...
This a amazing book if your just looking for primary and formative knowledge about Data Analytics. This book is simple to read and process filled with a lot of true life examples about how each subject is applied in business.
It is just an introduction to data analytics. If you already focus on the news about data analytics, you found nothing more than you already knew.
This book does not teach you how to use huge data analytics. It attempts to teach you ABOUT huge data analytics and does a very not good job at even reads like the author read some Wikipedia pages about huge data and place them into his own words (without any true knowledge on the subject). He then realized his word count was half of what his editor wanted so he added pointless sentences (eg: "Depending on your business, its size and the product and services provided, primary statistical info will have more or less significance." My apologies for wasting your time having to read that) and countless reiterations ("In chapter X I told you about[...]" over and over... yea, I read that chapter 20 mins earlier and you've repeated that same info 8 times since then already). If edited properly this already short book would have been a quarter the length.
It is a decent book. Amazing clarified models that you can use with other programming dialects. Valuable to anybody. Needed only a small persistence on the off possibility that you are not used to utilizing exceed expectations. I am utilizing it to present info examination to my significant other. Yet, I am found out a amazing deal from it.
An abuse of cash and time. Incapably made. Three clear syntactic mistakes on the plain first page of the Introduction.. Nothing valuable picked up from perusing this short book. It has all the earmarks of being an independently published blog passage.
There are so a lot of sophisticated tools and techniques to handle growing volume of data that generates from social e book inspired me more to discover the knowledge of Machine Learning and Data Mining and I'm eager to obtain a hands on experience as a data engineer.
This is an excellent, very precise and detailed book. The book is well-structured, gives me the full knowledge of huge data and the technique on how to analyze the data which is very useful for my job.
This book content is very simple to understand and very informative. A lot of info in this book. After reading this book and learn a lot of things. I really enjoyed read this book. Thanks author!
This book will enable you to learn and see more about Data Analytics. I have a decent perception of the subject in the wake of perusing this book and would prescribe it to everybody who is amazing to go.
A waste of cash and time. Poorly written. Three obvious typos on the very first page of the Introduction. Nothing useful gained from reading this short book. It appears to be a self-published blog entry.
Useful for people with primary engineering or technical skills as an introduction to various techniques and use cases for data science
I didn't understand how I could use this book.I didn't search here any suitable examples.I didn't search here even one formula or something like that.Just a speech on data analytics is cool. Ok, I understood. But what can I do with it?Probably, if you are a novice, you'll search something. I couldn't.
This is by far the best book out in shop to obtain you started with using python for data science. You will need some primary understanding of python and machine learning to understand concepts here, but this book will definitely take you skill to next is is no-nonsense book and goes deep into items which are relevant and necessary to do data science in python, every page is rich in info and provides practical use case, optimization tricks and adds fresh dimensions to your understanding of topic.
I have used R for a few years and this was my first book that covered Python for data science. Even though it does not go into super amazing depth in any area, it is definitely a super book. It covers everything from Pandas, Matplotlib, and scikit-learn. I would highly recommend it for anyone that is fresh to Python and/or data science. The book is written with Jupyter Notebooks so it is simple to follow along and test code from the book in your own notebook.
I truly delighted in this book. I had very small involvement with python preceding perusing the book anyway I had the option to lift it up rapidly. After a short time I was plotting appropriations of continuous insights and prototypes a prescient displaying smaller scale administration. I think about this as an absolute necessity have book for any hopeful info researcher.
The author breaks things done into easy simple to understand was entertaining and highly educational. I especially appreciated the effort created by the author to walk a newbie through installation of a fresh programming environment .. An elegantly composed book giving a decent broad comprehension.
This book is carefully written to support you master the core concepts of Python programming and utilize your coding skills to analyze a huge volume of data and uncover valuable info that can otherwise be easily lost in such volume even if you have never learned any programming languages before.
This book is exceptionally elegantly composed by the writer and I very prescribe this book to every one of you is is the most informative book on python that I have ever purchased. You will be astonished how muсh you can dо in this dialect оnсе уоu knоw the rudiments.
This is excellent for people who have never started. Very informative in an simple to understand. it held very necessary content. I think this is a amazing book to begin the Ultimate Beginners’ Tutorial to Learning Python Data Science! I started this method of reading. I would recommend this book to anyone.
I ended up searching around on the author's and he does have all of the source code in a zip file. Simple book to support you begin understanding Data Science. I like this book. This book helped explain everything and even had the output of the code to present what each code block would do.
I only expect it to obtain better and better. continually backs up data viz theory with real-life samples, contrasting the amazing with the bad. I've already implemented a lot of of these data viz best practices in my line of prove the method you visualize your data .
Vanderplas provides a amazing overview of the standard libraries and concepts required to work with data effectively in Python. Worthwhile purchasing for an introduction or refresher on topics. Also, he has provided the code in helpful notebook form on Github.
I was expecting this book to have more info on becoming a data scientist. More on how to pull from SQL, and place into a language, or how to clean up a data set. Upon reading, I search that its more about buzz words for newcomers of the Computer Science field. Unless you just wish a dictionary to support explain the terms simply, I would not recommend the buy.
Simply a listing of skills necessary, not a how to book I was expecting from the title.
If you are looking into true dive into data science skip this book. You can google most of the information.
Lacking in specifics. Author throws lists of breezy generalizations at the page. Doesn't live up to the title. Proofreading very sloppy.
Neural networks and algorithms are described in an simple method with program examples, I'm learning python and working with neural networks, its a helpful resource for students.
This book is very practical and helpful. It includes the python pseudo code for a lot of primary Data Analysis From Scratch With Python, which was exactly what I was looking for. It would be helpful to have more info of what libraries commands come from. Recommend it .
Nice read! I genuinely trust there is a more noteworthy measure of such kind of book out there!good just in case you have to use the major e writer talked about here well ordered that exceptionally accommodating.
It is known from this book. I truly trust there is a greater amount of such sort of book out there!good just on the off possibility that you need to utilize the fundamental e author discussed here step by step that very helpful.
A very general and useful overview about data science. But not much more beyond this level. I think it is more like a collection of commonly used terms.
The primary thesis of "Everybody Lies" is that online data on human behavior, including Google searches and data from Facebook, shopping and pornographic sites, can reveal much about what we really think than data from surveys in which people might be too embarrassed to tell the truth. In our unguarded moments, when we are alone and searching Google in the privacy of our homes, we are much more likely to divulge our innermost desires. The premise is that truly understanding human behavior by method of psychology or neuroscience is too complicated right now, so it's much better to simply bypass that kind of understanding and look at what the numbers are telling us in terms of what people's online behavior. In doing this the author looks at a remarkable dozens of online sources and studies by leading researchers, and one must congratulate him for the diversity and depth of material he has plumbed.What has allowed us to access this pool of unguarded opinions and truckloads of data concerning human behavior is the Internet and the tools of "big" data. As the author puts it, this data is not just "big" but also "new", which means that the kind of data we can access is also quite various from what we are used to; in his words, we live in a globe where every sneeze, cough, internet purchase, political opinion, and evening run can be considered "data". This makes it possible to try hypotheses that we could not have tested before. For instance, the author gives the example of testing Freud's Oedipus Complex through accessing pornographic data which indicates a measurable interest in incest. Generally speaking there is quite an emphasis on exploring human sexuality in the book, partly because sexuality is one of those aspects of our life that we want to hide the most and are also pruriently interested in, and partly because investigating this data through Google searches and pornographic websites reveals some rather bizarre sexual preference that are also sometimes specific to one country or another. This is a somewhat fun use of data exploration can both reveal the obvious as well as throw up unexpected observations. A more serious use of data tools concerns political opinions. Based on Google searches in particular states, the author shows how racism (as indicated by racist Google searches) was a basic indicator of which states voted for Obama in the 2008 election and Trump in the 2016 election. That's possibly an obvious conclusion, at least in retrospect. A more counterintuitive conclusion is that the racism divide does not seem to map neatly on the urban-rural divide or the North-South divide, but rather on the East-West divide; people seem to be searching much more for explicitly racist things in the East compared to the West. There is also an interesting survey of gay people in more and less tolerant states which concludes that you are as likely to search gay people in both parts of the country. Another interesting section of the book talked about how calls for peace by politicians after terrorist attacks actually lead to more rather than less xenophobic Google searches; this is accompanied by a section that tips at how the trends can be potentially reversed if various words are used in political speeches. There is also an interesting discussion of how the belief that newspaper political leanings drive customer political preferences gets it exactly backward; the data shows that customer political preferences shape what newspapers print, so effectively they are doing nothing various from any other customer-focused, profit making e basic tool for doing all this data analysis is correlation or regression analysis, where you look at online searches and test to search correlations between certain terms and factors like geographic location, gender, ethnicity. One hopes that one has separated the most necessary correlated variable and has eliminated other potentially necessary ere are dozens of other amusing and informative studies - sometimes the author's own but more often other people's - that reveal human desires and behavior across a wide swathe of fields, including politics, dating, sports, education, shopping and sexuality. There's plenty of potentially useful material in these studies. For instance, some of the data that indicates gaps in educational or social attainment in various parts of the country are immediately actionable in principle. Google searches have also been used to hold track of flu and other disease epidemics. Sometimes finding correlations is financially lucrative; there is a story about how a horse expert found that success in horse races seems to correlate with one factor more than any other: the size of the left ventricle. Another study isolated the impact of the early growing season on the quality of wines. There is no doubt that financial firms, supermarkets, newspapers, hospitals and online purveyors of everything from pornography to peanuts are going to hold a close eye on this data to maximize their reach and nerally speaking I enjoyed "Everybody Lies"; for the scope of the material, the easy-going style and some of the counterintuitive observations it reveals. My main reservation about the book is that I think the author overstates his case and sometimes sounds a small too breathless about the amazing changes these tools are going to bring. More than once he uses the term "revolutionary" in describing these data tools, but I am much more suspicious of their ultimate utility. Firstly, data does not equal knowledge; rather, it is the raw material for knowledge. As the author himself acknowledges, understanding correlation is not the same as understanding causation, and it's in very few cases that a real causal relationship between people's Google searches and their real nature can be established. Part of the reason I think this method is because I don't believe that a person's Google find is as reflective of their innermost desires as the book seems to think, so what a person truly believes may go method beyond their online behavior. Consider the studies revealing people's sexual preferences for instance; how a lot of of them point to trivial idiosyncrasies and how a lot of are indicative of some deeper truth about human brains? The tools alone cannot draw this distinction. At the end of the day you could thus end up with a lot of data (including a lot of noise), but teasing apart the useful data points from the red herrings is a completely various matter. In this sense, looking at Google searches and other info can be a reductionist and simplistic condly, it's usually quite hard to control for all possible variables that may reflect a Google search; for instance in concluding that racism contributes the most to a particular political behavior, it's very hard to tease out all other factors that also may do so, especially when you are talking about a heterogeneous collection of human beings. How can you know that you have corrected for every possible factor? Thirdly and finally, the "science" part of "data science" still lacks rigor in my opinion. For instance, a lot of the conclusions the book talks about are based on single studies which don't seem to be repeated. In some cases the sample sizes are large, but in other cases they are small. Plus, people's opinions can change over time, so it's necessary to pick the right time window in which to do the study. All this points to amazing responsibility on the part of data scientists to create sure that their results are rigorous and not too simplistic, before they are taken up by both politicians and the general public as blunt instruments to change social policies. This responsibility increases especially as these approaches become more widespread and cheaper to use, especially in the hands of non-specialists. When you are in possession of a hammer, everything starts looking like a nsidering all these caveats, I thus search tools like those described in this volume to be the starting points for understanding human behavior, rather than direct determinants of human behavior. The tools themselves can tell you what they can be used for, not necessarily what issues would benefit the most from their application. The a lot of interesting studies in this book certainly respond the "what" quite well, but most of them are still quite far from answering the "how" and especially the "why". They point out the path to the door, but don't necessarily tell us which door to open. And they can be especially impoverished in illuminating what lies beyond; for that only a real understanding of the human mind will pave the way.
I read it in two days. It is an simple and fun read even for the general reader.“Everybody Lies” is a fascinating dive into the globe of “Big Data”. The core premise of the book is that by mining huge data sets we can respond questions more accurately than through other methods. Behavioral and psychological questions can be addressed without the filter of a poll or questionnaire, where “everybody lies”. Thus, in theory, we capture a more accurate representation of people’s true prejudices and desires through huge data searches than through th Stephens-Davidowitz uses quirky and often humorous examples to present the power of huge data. One example from the book revealed that I was one of the 7% who finished “Thinking, Quick and Slow” (I am not sure whether that is a amazing or poor thing).The data is the data, but the interpretation is subjective. My concern is that the subjective conclusions drawn from the data will be presented as fact rather than what they are – subjective interpretations of the data (however statistically significant). As such, there is a danger that such info will be misused. We still need to be cautious in determining the meaning of the th Stephens-Davidowitz brings the subject to life with terrific story telling about a wide number of subjects. The author has performed a amazing service by making this very necessary subject comprehensible to “the rest of us”.
A small long on commentary but simple read through. There is a lot of location left unexplored which is the frustrating part. The fact that everybody lies is painfully obvious. I hope pulling back the curtain eventually helps to improve our bullpucky addled world.Enjoy that beer, Seth.
This was one of the entertaining books I've read in quite a while. In diving deeply into find history data, Stephens-Davidowitz not only reveals that people's actions trump their beliefs or words, but he presents it in such a disturbingly hilarious method that I go through the entire book in less than two days. I found myself bookmarking pages for reference later, something I very rarely do when reading. Not only would I recommend this book to everyone, but I will surely be re-reading this again sometime soon.
This is an perfect book about huge data research. It starts the conversation about what we can learn, and what we can't, from databases of digitized data. Without a doubt, this is an necessary book to read for anyone who uses a computer and/or does research. It will create your think twice about the info that we leave out and about on the Internet. At the very least, this book is full of perfect conversation starters for any nerdy parties you might attend.
Well written description of how huge data is already changing our lives even if we don't know it, for amazing and bad. The book is simple to read, understand, and will change the method you see the electronic world, as well as then growing globe of data science.
The book "Everybody Lies: Huge Data, Fresh Data, and What the Internet Can Tell Us About Who..." is an perfect approximation to this fresh globe of the Huge Data through the enormous amount of info that ourself deposit in the social networks. The reading is enjoyable and is a page turner. Highly recommend.
What can I say? I loved this book! If you have any curiosity about how the globe works or why people do the things that they do, you will love this book too. Who does not wish to be able to create accurate predictions about the behavior of others? Seth Stephens-Davidowitz introduces us to the emerging scientific field of data science and how it can be used to respond questions that it have heretofore been unanswerable. He does not shy away from trying to respond more socially difficult questions. But he does it in a very entertaining way. Think of it as Moneyball for not only baseball but literally everything else in the world.
Well written, very timely, rich with anecdotes, and covers the Huge Data's march through the current technology climate. Gave me anecdotes to intersperse my own presentations with, for cogent, persuasive arguments
A surprisingly insightful and often amusing examination of the Internet data explosion. Yes, it's a small wonky but you don't have to be statistician or sociologist to have fun this book.
Amazing one, being in a globe where technology rules, we don't realize what is going on in the background. I mean sure you have conspiracy theorists that believe Alexa works for the CIA and such. But in reality everything we do is being monitored in some method or function. This book is an eye-opener as to some of the ways our info is taken from us and being used. Some of the ways featured in this book I had absolutely no clue that was happening. I mean we have all noticed that if we look something up on Google, that following that Fb starts to use ads targeting something we are already interested in. This is a amazing book to read if you wish to know how and why your info is taken and used. Thankful! very nice one !
I strongly recommend this book for your business based library. The detailed examples and simple to understand language really helped me and it created statistics, a difficult topic to comprehend and conquer, so simple for me. If you wish to start making ultimate business decisions relying on figures and numbers, this complete beginner's tutorial to statistical science will bring amazing advantage to you.
Having read a couple of introductory books to statistics, it was refreshing to search a book for beginners that is simple and clear to follow without the author trying too hard to create statistics so-called “fun” & “entertaining”. For me, the historical context added to this book was very insightful and for the most part, the author explains how the different concepts tie in with one another. The further resources section could be more extensive – it seemed more like an afterthought – but all in all an perfect introduction to inferential statistics.
This book is an eye-opener as to some of the ways our info is taken from us and being used. Some of the ways featured in this book I had absolutely no clue that was happening. I mean we have all noticed that if we look something up on Google, that following that Fb starts to use ads targeting something we are already interested in. This is a amazing book to read if you wish to know how and why your info is taken and used.
I emphatically suggest this book for your business based library. The point by point models and straightforward language truly helped me and it created measurements, a troublesome topic to grasp and vanquish, so natural for me. On the off possibility that you need to begin settling on extreme business choices depending on figures and numbers, this total apprentice's manual for factual science will carry extraordinary preferred position to you.
THE ART OF INVISIBILITY is a small bit scary. The authors, Kevin Mitnick and Robert Vamosi, document the myriads of ways that others can spy on our activities. You might think no one knows what you are doing, but you are wrong: "Each and every one of us is being watched." If you carry a cell phone, "You are being surveilled."Mitnick tells the story of how the popular John McAfee, on the lam, was found supposedly by coordinates listed in the meta data of a image posted online. The authors snicker, "Take it from me: if you’re trying to obtain off the grid and totally disappear, you don’t wish to begin a blog."Some of the pointers are beautiful basic, such as using powerful passwords, and being careful to setup your home Wireless connection using the recent security protocols. A huge chunk of the book relates to securing wireless internet access. "Public Wi-Fi wasn’t made with online banking or e-commerce in mind. It is merely convenient, and it’s also incredibly insecure."More advanced suggestions are for those who feel they need extreme online privacy. These strategies contain things such as using "burner" phones, paid for with cash, and using encryption tools to hide the data on our enforcement has come a long method in tracking down fugitives. The authors explain how authorities use devices to mimic cellular base stations, and "designed to intercept voice and text messages." Using another tactic, the FBI has successfully tracked criminals by getting the cell turret data, and correlating their cell phone records.I was surprised to learn of certain latest laws regarding data preservation. In the happening of a legal investigation, you must preserve your entire browser history. You can be arrested--and people have been, for clearing the e really meaty parts of the book provide extreme strategies to remain anonymous on the internet. Mitnick advises creating a complete fresh persona, "one that is completely unrelated to you. . . When you’re not being anonymous, you must also rigorously defend the separation of your life from that anonymous identity."The first thing to do in making yourself anonymous is to obtain a cheap standalone laptop--used only for your anonymous persona. "Don't ever use the anonymous laptop at home or work. Ever."Here are a few more hints for becoming anonymous:* When you travel, don't bring electronics that shop sensitive info with you.* Encrypt the confidential data on your e authors show a LOT of various ways to create your online persona more invisible. The authors admit, however, that even with all their precautions, it is still tough to be 100% anonymous. The main idea is to create it much more difficult for the intruder. So, place up "so a lot of obstacles that an attacker will give up and move on to another target. . . Being anonymous in today’s digital globe requires a lot of work and constant vigilance."All in all, I found THE ART OF INVISIBILITY to be an interesting, fairly-practical read. It was amazing to be reminded about the proper setup of networks, and how vulnerable public systems can be. I don't feel the need to go out and buy a "burner" phone anytime soon, but it's amazing to vance Review Copy courtesy of the publisher.
Do you wish to understand the technological globe around you? Do you have concerns about what info is gathered about you? Are you disturbed by the lack of corporate responsibility? Are you disturbed that our systems of justice would have us believe that technologies are [somehow] an exception to our Constitutional protections or our rights to privacy? Do you have something to protect even though you may not necessarily have nothing to hide? Do you wish to reign in the info gathered about you? Do you just wish to disappear? Don't know where to start?Hello, world. This is where your journey begins. Where it ends, is entirely up to e Art of Invisibility is a amazing read for anyone who answered yes to any or all of the questions I've posted above. Consider it a primer, a starting point, an overview, or a step along a path. Whether you are an daily citizen, a concerned parent, a privacy advocate, or getting a begin in info security, Kevin Mitnick lays out some basics and practicals for, well, disappearing -as a means of safeguarding the info about you that so a lot of companies seek to benefit from, yet lack the responsibility to wield or even safeguard.Ensuring your security and privacy isn't a "set it and forget it" -thing, it is a process, a method of life, but do not allow that fact overwhelm you because the rewards are amazing and, in the end, YOU are the one in control. And control, dear reader, starts with have a right to protect yourself and your interests (and we all know that companies like Equifax won't). So, let's obtain your started, shall we?
Amazing introduction to protecting our privacy in an age where both corporate and government invasiveness threatens individual autonomy. This book reveals a lot of of the ways huge data, amassed from our online activity, which often we unknowingly give consent to third-parties to possess and profit from, can have unwanted consequences from identity theft to a ruined credit rating, to corporate espionage. It is also a wake up call for parents to teach there children safe practices around cell phone use and online activity which can expose them to undue harm. One of the issues with such a book is it quickly falls out of date due to the every changing pace of digital communications technology.
This book has something for the simply curious to those looking for how-to instructions. It is informative to see just how broad and deep surveillance goes in modern society. If privacy and security interest you daily, this book is a must read. Even if you will not do everything presented, you will be better informed.
The book blends primary info about achieving anonymity with specific instructions and tool recommendations. I would have loved to see more detail, but it's a amazing read for those interested in understanding how data about you is gathered and potentially used versus you.
Interesting read. Amazing explanations about privacy in the age of computers. Mitnick provides a lot of useful info which is eye opening. If you want to go to the extreme to protect your privacy, or just learn how be more sensible with your private information, he tells you how to go about it.
This book is one that all people who are concerned about cyber security should read. I feel we each who takes it seriously will take away something of value. You decide!
Kevin provides perfect insight into the dozens of ways that we are all being tracked and how data can be used to possibly understand us better than we understand ourselves. Two major themes are recurring throughout the book as to the why. Theme one is surveillance. Theme two is advertising/marketing. One thing is crystal clear. Technological advances have changed the globe in dramatic ways. Some of these changes will become readily apparent after reading this book. Interesting and amazing to know.
Scares the hell out of anyone with electronic contract with the world. Caution, if you install the anit-hacking software you will not be able to do anything involving the internet with your computer, easily.
I was looking for a book to support learn some fresh skills relevant to some current projects - I selected this one due to a lot of positive reviews. After receiving it and reading the first section, I don't really know what to say. It feels alot like this book has been run through Google Translate several times through difficult to translate languages. A very difficult read with a lot of glaring errors - the sentence structure and grammar is just so bad, I just can't believe I'm actually looking at this on physical pages of paper. At best this should be an ebook which appears unsolicited in your email inbox. I am not sure where all the 5 star reviews came from, I can only assume they must be fake.I actually believe someone has setup an AI to write a book about Machine Learning and then post fake amazon reviews. It feels like information scoured from the internet and e-duct-taped together into a semi-intelligible form. While, if actually done by AI, that's beautiful impressive and they should consider writing an actual book about that - I might suggest whoever did this should probably also learn how to integrate some type of sentence structure correction tool or at least run it through grammarly.. or even.. God forbid... Microsoft Word... prior to publishing it.P.S. And this is coming from a redneck - I can only imagine what an English professor would have to say.
I bought this book to support me obtain up and running fast for a project in an "Introduction to Machine Learning" independent study course. Of the books I bought for the same task, this was by far the most helpful for building practical machine learning applications.
First, don't be fooled by all the fake 5 star reviews of this book. It fooled me and I am sorry I wasted my money. The content of the book is okay at best and hence the reason I give it a 2 star rating instead of 1 star. It was so damn confusing and hard to read the book with all the grammatical errors and outright misuse of the English language. My guess is that either someone used AI to write this book from available information on the web or the "author" does not have a very amazing grip on the English language or the author used a translation service to obtain it into "English". Just don't waste your time with this book or its exact clone "Machine Learning" by Steven Samelson (fake author name--same as Lilly Trinity). The books are both basically the same number of pages, both self published, and both printed in Lexington, KY in 2019
This is extremely an awesome book. The book itself is a genuinely speedy perused and can be handled in an evening on the off possibility that it keeps your advantage and the visual models and clear directions created the remainder of the book a breeze to pursue. Despite the fact that it was anything but difficult to pursue, I don't feel like I missed out on specialized substance a for an abnormal state presentation, it was brief and definite and it was engaging and exceedingly instructive and I particularly valued the exertion created by the creator to walk a novice through establishment of another programming condition and after that utilizing it to deliver something helpful.
This is one of the poorest excuses for a book I have seen in years. It appears someone just searched for a bunch of unrelated information about machine learning online, changed a few words around, and pasted it together. It was clearly assembled by a non-native English speaker and is absolutely loaded with grammatical and typographical errors.I ordered the book after seeing a positive overall review score, but after going back and looking at the reviews carefully, the huge majority appear fake. Some are even just positive reviews of various machine learning books that have been copied verbatim with the wrong author's name left in! I expect Amazon will eventually remove these suspicious reviews, but in the mean time, stay away!
It's informative tutorial to learn about machine learning. It's simple to follow. The field of machine learning is very huge and is developing very rapidly every day. It continues to evolve day by day, and the campaign continues to honor fashion. From its use in robotics to data extraction and finance, the word has become more a slogan than a field of study. Today, artificial intelligence (AI) is used everywhere. It should not be confused that the main applications of AI are machine learning (ML), in which computers, software, and peripherals act through an integrated cognitive process, related to that of the human brain. But machine learning applications are far from being used on the platform, software and robotic devices. Beginner’s Tutorial to Machine Learning.
This is an instructive book. The book writer well clarification in this book about Machine Learning. Every latest bit of it is essential straightforward English so I won't require a special coding degree to obtain it. Here, This book all the essential passage level points needed for unquestionably the novice so I can start to comprehend this exceedingly imaginative innovative progression. I am satisfied to buy this book. Much obliged creator.
The book author well-explanation in this book about Machine Learning and all of it is very primary easy English so I won’t need a unique coding degree to understand it and this book has added a lot of exceptional recipes and also helpful for all of us and the data channel must be governed by control rules and understand where the data will be physically located and where machine learning will take put and countries require that citizens data be kept in the country and this data helps each business and technical leaders search out how to use machine learning to anticipate and predict the future and if you're searching for simply a primary guide, then this book is perfect.
This is really an perfect book. The book itself is a fairly fast read and can be tackled in an afternoon if it keeps your interest and the visual examples and clear instructions created the rest of the book a breeze to follow. Although it was simple to follow, I don’t feel like I lost out on technical content an for a high-level introduction, it was concise and detailed and it was entertaining and highly educational and i especially appreciated the effort created by the author to walk a newbie through installation of a fresh programming environment and then using it to produce something useful.
Satisfied to offer this book a glowing endorsement to beginners. Nothing in this book is intimidating. I was worried that I might obtain lost halfway through after the author started introducing the different algorithms. But no, this is where the book got significantly better. The visual examples and clear instructions created the rest of the book a breeze to follow. Although it was simple to follow, I don’t feel like I lost out on technical content. For a high-level introduction, it was concise and detailed.
Most teachers say they wish to support students develop reasoning and problem-solving skills. This book provides guidance on how to accomplish this goal. Removed are lectures, memorization, and math problems. Instead, students are taught to take what they recognize about the natural globe around them and apply it to the discipline of physics. It helped me to better understand the fundamentals and was extremely clear and simple to comprehend. Deep Learning is a subfield of machine learning concerned with algorithms inspired by the structure and function of the brain called artificial neural networks. It serves as both an education and a reference book.
Interesting! The book will teach you as a layman so it is the best book to pick if you have just stepped into the globe of artificial intelligence or wish to know about it in general. This book has a very simple to understand language with a straight forward approach. It is helpful for every person who is keen to learn and know about artificial intelligence and neural networks.
Very well written and simple to read this book. A lot of necessary info in this book. I like this book. I highly recommended this book for anyone who has interested in Deep Learning.
A amazing introduction to deep learning for individuals without PhDs. Excellent for those who simply wish to train, tune, and deploy deep learning models without needing to understand complex theory. There's a lot of useful info in this book. Very well written and written from a practical perspective of those actually creating the models. Amazing book! Very useful to have it next to you when you are learning, implementing or using.
This is an amazing artificial intelligence book for the beginner learner. Wonderful prologue to machine learning and It's gives me give some supportive indications and similar I wish to prescribe this book to all.
This book provides guidance on how to accomplish this goal. Removed are lectures, memorization, and math problems. Instead, students are taught to take what they recognize about the natural globe around them and apply it to the discipline of physics. By reading this book I have learned more from this book very easily. Thanks author for creating us a fresh book for all of us!
Perfect overview. This book is of appropriate depth and breadth and is the first of its kind, i.e., an academic treatment of deep learning. Primary concepts are explained in the book so it is self-contained and covers the deep learning field. If you are an expert, then another books may better, but if you wish to learn about Deep Learning, I recommend it.
Very comprehensive, and focussed on what really matters. Rather than filling in with redundant examples that you could easily search on the web, this book gives you everything else that you need. The rationale for algorithms, their motivation and derivation. This is both thorough and readable. It serves as both an education and a reference book.
This book is a amazing introduction to a subject that I have some primary info about already, but wish to know more about. I like this one...