Book picks similar to
Python Machine Learning: Python Machine Learning From Scratch: Step by Step Guide with Scikit-Learn and TensorFlow by Daniel Nedal
computers
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ai-and-data-science
The Best of 2600: A Hacker Odyssey
Emmanuel Goldstein - 2008
Find the best of the magazine's writing in Best of 2600: A Hacker Odyssey, a collection of the strongest, most interesting, and often most controversial articles covering 24 years of changes in technology, all from a hacker's perspective. Included are stories about the creation of the infamous tone dialer "red box" that allowed hackers to make free phone calls from payphones, the founding of the Electronic Frontier Foundation, and the insecurity of modern locks.
How to Count (Programming for Mere Mortals, #1)
Steven Frank - 2011
unsigned numbers- Floating point and fixed point arithmeticThis short, easily understood book will quickly get you thinking like a programmer.
WordPress: The Missing Manual
Matthew MacDonald - 2012
This jargon-free Missing Manual shows you how to use WordPress and its themes, plug-ins, and widgets to build just about any website you can imagine, from a classy blog to a basic e-commerce site.The important stuff you need to know:Create a blog. Get a free WordPress.com account, choose the right theme, and start publishing content.Build a website. Produce a professional-looking business site by customizing a WordPress theme.Add features. Choose from thousands of WordPress widgets and plug-ins to extend your site’s features.Mix in multimedia. Include slideshows, video clips, webcasts, podcasts, and music players.Involve your readers. Let readers leave comments, contribute to your site, and carry on a dialog.Build an audience. Learn search-engine optimization, measure your reader’s favorite pages, and publicize your site.Create a community. Use social media tools such as “Like” and sharing buttons, and provide RSS feeds of your posts.
Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die
Eric Siegel - 2013
Rather than a "how to" for hands-on techies, the book entices lay-readers and experts alike by covering new case studies and the latest state-of-the-art techniques.You have been predicted — by companies, governments, law enforcement, hospitals, and universities. Their computers say, "I knew you were going to do that!" These institutions are seizing upon the power to predict whether you're going to click, buy, lie, or die.Why? For good reason: predicting human behavior combats financial risk, fortifies healthcare, conquers spam, toughens crime fighting, and boosts sales.How? Prediction is powered by the world's most potent, booming unnatural resource: data. Accumulated in large part as the by-product of routine tasks, data is the unsalted, flavorless residue deposited en masse as organizations churn away. Surprise! This heap of refuse is a gold mine. Big data embodies an extraordinary wealth of experience from which to learn.Predictive analytics unleashes the power of data. With this technology, the computer literally learns from data how to predict the future behavior of individuals. Perfect prediction is not possible, but putting odds on the future — lifting a bit of the fog off our hazy view of tomorrow — means pay dirt.In this rich, entertaining primer, former Columbia University professor and Predictive Analytics World founder Eric Siegel reveals the power and perils of prediction: -What type of mortgage risk Chase Bank predicted before the recession. -Predicting which people will drop out of school, cancel a subscription, or get divorced before they are even aware of it themselves. -Why early retirement decreases life expectancy and vegetarians miss fewer flights. -Five reasons why organizations predict death, including one health insurance company. -How U.S. Bank, European wireless carrier Telenor, and Obama's 2012 campaign calculated the way to most strongly influence each individual. -How IBM's Watson computer used predictive modeling to answer questions and beat the human champs on TV's Jeopardy! -How companies ascertain untold, private truths — how Target figures out you're pregnant and Hewlett-Packard deduces you're about to quit your job. -How judges and parole boards rely on crime-predicting computers to decide who stays in prison and who goes free. -What's predicted by the BBC, Citibank, ConEd, Facebook, Ford, Google, IBM, the IRS, Match.com, MTV, Netflix, Pandora, PayPal, Pfizer, and Wikipedia. A truly omnipresent science, predictive analytics affects everyone, every day. Although largely unseen, it drives millions of decisions, determining whom to call, mail, investigate, incarcerate, set up on a date, or medicate.Predictive analytics transcends human perception. This book's final chapter answers the riddle: What often happens to you that cannot be witnessed, and that you can't even be sure has happened afterward — but that can be predicted in advance?Whether you are a consumer of it — or consumed by it — get a handle on the power of Predictive Analytics.
Coding Interview Questions
Narasimha Karumanchi - 2012
Peeling Data Structures and Algorithms: * Programming puzzles for interviews * Campus Preparation * Degree/Masters Course Preparation * Instructor's * GATE Preparation * Big job hunters: Microsoft, Google, Amazon, Yahoo, Flip Kart, Adobe, IBM Labs, Citrix, Mentor Graphics, NetApp, Oracle, Webaroo, De-Shaw, Success Factors, Face book, McAfee and many more * Reference Manual for working people
Machine Learning: An Algorithmic Perspective
Stephen Marsland - 2009
The field is ready for a text that not only demonstrates how to use the algorithms that make up machine learning methods, but also provides the background needed to understand how and why these algorithms work. Machine Learning: An Algorithmic Perspective is that text.Theory Backed up by Practical ExamplesThe book covers neural networks, graphical models, reinforcement learning, evolutionary algorithms, dimensionality reduction methods, and the important area of optimization. It treads the fine line between adequate academic rigor and overwhelming students with equations and mathematical concepts. The author addresses the topics in a practical way while providing complete information and references where other expositions can be found. He includes examples based on widely available datasets and practical and theoretical problems to test understanding and application of the material. The book describes algorithms with code examples backed up by a website that provides working implementations in Python. The author uses data from a variety of applications to demonstrate the methods and includes practical problems for students to solve.Highlights a Range of Disciplines and ApplicationsDrawing from computer science, statistics, mathematics, and engineering, the multidisciplinary nature of machine learning is underscored by its applicability to areas ranging from finance to biology and medicine to physics and chemistry. Written in an easily accessible style, this book bridges the gaps between disciplines, providing the ideal blend of theory and practical, applicable knowledge."
Bayes Theorem: A Visual Introduction For Beginners
Dan Morris - 2016
Bayesian statistics is taught in most first-year statistics classes across the nation, but there is one major problem that many students (and others who are interested in the theorem) face. The theorem is not intuitive for most people, and understanding how it works can be a challenge, especially because it is often taught without visual aids. In this guide, we unpack the various components of the theorem and provide a basic overview of how it works - and with illustrations to help. Three scenarios - the flu, breathalyzer tests, and peacekeeping - are used throughout the booklet to teach how problems involving Bayes Theorem can be approached and solved. Over 60 hand-drawn visuals are included throughout to help you work through each problem as you learn by example. The illustrations are simple, hand-drawn, and in black and white. For those interested, we have also included sections typically not found in other beginner guides to Bayes Rule. These include: A short tutorial on how to understand problem scenarios and find P(B), P(A), and P(B|A). For many people, knowing how to approach scenarios and break them apart can be daunting. In this booklet, we provide a quick step-by-step reference on how to confidently understand scenarios.A few examples of how to think like a Bayesian in everyday life. Bayes Rule might seem somewhat abstract, but it can be applied to many areas of life and help you make better decisions. It is a great tool that can help you with critical thinking, problem-solving, and dealing with the gray areas of life. A concise history of Bayes Rule. Bayes Theorem has a fascinating 200+ year history, and we have summed it up for you in this booklet. From its discovery in the 1700’s to its being used to break the German’s Enigma Code during World War 2, its tale is quite phenomenal.Fascinating real-life stories on how Bayes formula is used in everyday life.From search and rescue to spam filtering and driverless cars, Bayes is used in many areas of modern day life. We have summed up 3 examples for you and provided an example of how Bayes could be used.An expanded definitions, notations, and proof section.We have included an expanded definitions and notations sections at the end of the booklet. In this section we define core terms more concretely, and also cover additional terms you might be confused about. A recommended readings section.From The Theory That Would Not Die to a few other books, there are a number of recommendations we have for further reading. Take a look! If you are a visual learner and like to learn by example, this intuitive booklet might be a good fit for you. Bayesian statistics is an incredibly fascinating topic and likely touches your life every single day. It is a very important tool that is used in data analysis throughout a wide-range of industries - so take an easy dive into the theorem for yourself with a visual approach!If you are looking for a short beginners guide packed with visual examples, this booklet is for you.
Darwin Among The Machines: The Evolution Of Global Intelligence
George Dyson - 1997
Dyson traces the course of the information revolution, illuminating the lives and work of visionaries - from the time of Thomas Hobbes to the time of John von Neumann - who foresaw the development of artificial intelligence, artificial life, and artificial mind. This book derives both its title and its outlook from Samuel Butler's 1863 essay "Darwin Among the Machines." Observing the beginnings of miniaturization, self-reproduction, and telecommunication among machines, Butler predicted that nature's intelligence, only temporarily subservient to technology, would resurface to claim our creations as her own. Weaving a cohesive narrative among his brilliant predecessors, Dyson constructs a straightforward, convincing, and occasionally frightening view of the evolution of mind in the global network, on a level transcending our own. Dyson concludes that we are in the midst of an experiment that echoes the prehistory of human intelligence and the origins of life. Just as the exchange of coded molecular instructions brought life as we know it to the early earth's primordial soup, and as language and mind combined to form the culture in which we live, so, in the digital universe, are computer programs and worldwide networks combining to produce an evolutionary theater in which the distinctions between nature and technology are increasingly obscured. Nature, believes Dyson, is on the side of the machines.
Discrete Mathematical Structures with Applications to Computer Science
Jean-Paul Tremblay - 1975
MacBook For Dummies
Mark L. Chambers - 2006
In addition to the freedom to work wherever you happen to be, a MacBook offers youA portable darkroom with iPhoto Mobile music, podcasts, and Internet radio GarageBand software that lets you make your own music The ability to create and share original movies and DVDs Safari, a safer and ultra-cool Web browser, and all the other OS X advantages Whether you already have your new MacBook or are still weighing the pros and cons of various models, MacBook For Dummies is a valuable resource. For newcomers to laptop land, it's packed with basic information about using and caring for Mac laptops. It also walks you through Mac OS X, the revolutionary Macintosh operating system that makes your laptop tick. Then it's on to all the fun stuff you can do with your MacBook, like making music, editing photos and turning them into a book, creating DVDs on the road, or adding a wireless keyboard. MacBook For Dummies will help youSet up your MacBook and get acquainted with all the features of the Mac OS X Tiger operating system Use the Safari Web browser and Apple's .Mac Internet subscriber service, connect your MacBook to a printer, and communicate with your cell phone or PDA Connect to a wired or wireless network Make the most of the iLife applications that come with your MacBook--iTunes, iPhoto, iMovie HD, iDVD, and GarageBand Keep your MacBook and your data safe, troubleshoot any problems, and maintain your system Popular For Dummies author Mark Chambers has loaded this fun book with tips, ideas, and his famous "Mark's Maxims"--power user advice that will guide you around the pitfalls and make you a Macxpert in no time. From latptop basics all the way to upgrading and adding memory, MacBook For Dummies will be your MacBook's best friend.
The Success of Open Source
Steven Weber - 2004
Leaving source code open has generated some of the most sophisticated developments in computer technology, including, most notably, Linux and Apache, which pose a significant challenge to Microsoft in the marketplace. As Steven Weber discusses, open source's success in a highly competitive industry has subverted many assumptions about how businesses are run, and how intellectual products are created and protected.Traditionally, intellectual property law has allowed companies to control knowledge and has guarded the rights of the innovator, at the expense of industry-wide cooperation. In turn, engineers of new software code are richly rewarded; but, as Weber shows, in spite of the conventional wisdom that innovation is driven by the promise of individual and corporate wealth, ensuring the free distribution of code among computer programmers can empower a more effective process for building intellectual products. In the case of Open Source, independent programmers--sometimes hundreds or thousands of them--make unpaid contributions to software that develops organically, through trial and error.Weber argues that the success of open source is not a freakish exception to economic principles. The open source community is guided by standards, rules, decisionmaking procedures, and sanctioning mechanisms. Weber explains the political and economic dynamics of this mysterious but important market development.
Network Security Essentials: Applications and Standards
William Stallings - 1999
Covers e-mail security, IP security, Web security, and network management security. Includes a concise section on the discipline of cryptography-covering algorithms and protocols underlying network security applications, encryption, hash functions, digital signatures, and key exchange. For system engineers, engineers, programmers, system managers, network managers, product marketing personnel, and system support specialists.
Python Tricks: A Buffet of Awesome Python Features
Dan Bader - 2017
Discover the “hidden gold” in Python’s standard library and start writing clean and Pythonic code today.
Who Should Read This Book:
If you’re wondering which lesser known parts in Python you should know about, you’ll get a roadmap with this book. Discover cool (yet practical!) Python tricks and blow your coworkers’ minds in your next code review.
If you’ve got experience with legacy versions of Python, the book will get you up to speed with modern patterns and features introduced in Python 3 and backported to Python 2.
If you’ve worked with other programming languages and you want to get up to speed with Python, you’ll pick up the idioms and practical tips you need to become a confident and effective Pythonista.
If you want to make Python your own and learn how to write clean and Pythonic code, you’ll discover best practices and little-known tricks to round out your knowledge.
What Python Developers Say About The Book:
"I kept thinking that I wished I had access to a book like this when I started learning Python many years ago." — Mariatta Wijaya, Python Core Developer"This book makes you write better Python code!" — Bob Belderbos, Software Developer at Oracle"Far from being just a shallow collection of snippets, this book will leave the attentive reader with a deeper understanding of the inner workings of Python as well as an appreciation for its beauty." — Ben Felder, Pythonista"It's like having a seasoned tutor explaining, well, tricks!" — Daniel Meyer, Sr. Desktop Administrator at Tesla Inc.
The Rootkit Arsenal: Escape and Evasion in the Dark Corners of the System
Bill Blunden - 2009
Adopting an approach that favors full disclosure, The Rootkit Arsenal presents the most accessible, timely, and complete coverage of rootkit technology. This book covers more topics, in greater depth, than any other currently available. In doing so the author forges through the murky back alleys of the Internet, shedding light on material that has traditionally been poorly documented, partially documented, or intentionally undocumented.The spectrum of topics covered includes how to:* Hook kernel structures on multi-processor systems* Use a kernel debugger to reverse system internals* Inject call gates to create a back door into Ring-0* Use detour patches to sidestep group policy* Modify privilege levels on Vista by altering kernel objects* Utilize bootkit technology* Defeat live incident response and post-mortem forensics* Implement code armoring to protect your deliverables* Establish covert channels using the WSK and NDIS 6.0
Algorithms of the Intelligent Web
Haralambos Marmanis - 2009
They use powerful techniques to process information intelligently and offer features based on patterns and relationships in data. Algorithms of the Intelligent Web shows readers how to use the same techniques employed by household names like Google Ad Sense, Netflix, and Amazon to transform raw data into actionable information.Algorithms of the Intelligent Web is an example-driven blueprint for creating applications that collect, analyze, and act on the massive quantities of data users leave in their wake as they use the web. Readers learn to build Netflix-style recommendation engines, and how to apply the same techniques to social-networking sites. See how click-trace analysis can result in smarter ad rotations. All the examples are designed both to be reused and to illustrate a general technique- an algorithm-that applies to a broad range of scenarios.As they work through the book's many examples, readers learn about recommendation systems, search and ranking, automatic grouping of similar objects, classification of objects, forecasting models, and autonomous agents. They also become familiar with a large number of open-source libraries and SDKs, and freely available APIs from the hottest sites on the internet, such as Facebook, Google, eBay, and Yahoo.Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book.