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|The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)
Lowest new price: $43.92
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List price: $89.95
Author: Trevor Hastie
This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of colour graphics. It is a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book.
This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorisation, and spectral clustering. There is also a chapter on methods for "wide'' data (p bigger than n), including multiple testing and false discovery rates.
|Life 3.0: Being Human in the Age of Artificial Intelligence
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Author: Max Tegmark
New York Times Best Seller
How will Artificial Intelligence affect crime, war, justice, jobs, society and our very sense of being human? The rise of AI has the potential to transform our future more than any other technology—and there’s nobody better qualified or situated to explore that future than Max Tegmark, an MIT professor who’s helped mainstream research on how to keep AI beneficial.
How can we grow our prosperity through automation without leaving people lacking income or purpose? What career advice should we give today’s kids? How can we make future AI systems more robust, so that they do what we want without crashing, malfunctioning or getting hacked? Should we fear an arms race in lethal autonomous weapons? Will machines eventually outsmart us at all tasks, replacing humans on the job market and perhaps altogether? Will AI help life flourish like never before or give us more power than we can handle?
What sort of future do you want? This book empowers you to join what may be the most important conversation of our time. It doesn’t shy away from the full range of viewpoints or from the most controversial issues—from superintelligence to meaning, consciousness and the ultimate physical limits on life in the cosmos.
|Design Patterns: Elements of Reusable Object-Oriented Software
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Author: Erich Gamma
Brand: Erich Gamma
Capturing a wealth of experience about the design of object-oriented software, four top-notch designers present a catalog of simple and succinct solutions to commonly occurring design problems. Previously undocumented, these 23 patterns allow designers to create more flexible, elegant, and ultimately reusable designs without having to rediscover the design solutions themselves.
The authors begin by describing what patterns are and how they can help you design object-oriented software. They then go on to systematically name, explain, evaluate, and catalog recurring designs in object-oriented systems. With Design Patterns as your guide, you will learn how these important patterns fit into the software development process, and how you can leverage them to solve your own design problems most efficiently.
Each pattern describes the circumstances in which it is applicable, when it can be applied in view of other design constraints, and the consequences and trade-offs of using the pattern within a larger design. All patterns are compiled from real systems and are based on real-world examples. Each pattern also includes code that demonstrates how it may be implemented in object-oriented programming languages like C++ or Smalltalk.
Design Patterns is a modern classic in the literature of object-oriented development, offering timeless and elegant solutions to common problems in software design. It describes patterns for managing object creation, composing objects into larger structures, and coordinating control flow between objects. The book provides numerous examples where using composition rather than inheritance can improve the reusability and flexibility of code. Note, though, that it's not a tutorial but a catalog that you can use to find an object-oriented design pattern that's appropriate for the needs of your particular application--a selection for virtuoso programmers who appreciate (or require) consistent, well-engineered object-oriented designs.
|Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow, 2nd Edition
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Author: Sebastian Raschka
- Second edition of the bestselling book on Machine Learning
- A practical approach to key frameworks in data science, machine learning, and deep learning
- Use the most powerful Python libraries to implement machine learning and deep learning
- Get to know the best practices to improve and optimize your machine learning systems and algorithms
Machine learning is eating the software world, and now deep learning is extending machine learning. Understand and work at the cutting edge of machine learning, neural networks, and deep learning with this second edition of Sebastian Raschka's bestselling book, Python Machine Learning. Thoroughly updated using the latest Python open source libraries, this book offers the practical knowledge and techniques you need to create and contribute to machine learning, deep learning, and modern data analysis.
Fully extended and modernized, Python Machine Learning Second Edition now includes the popular TensorFlow deep learning library. The scikit-learn code has also been fully updated to include recent improvements and additions to this versatile machine learning library.
Sebastian Raschka and Vahid Mirjalili's unique insight and expertise introduce you to machine learning and deep learning algorithms from scratch, and show you how to apply them to practical industry challenges using realistic and interesting examples. By the end of the book, you'll be ready to meet the new data analysis opportunities in today's world.
If you've read the first edition of this book, you'll be delighted to find a new balance of classical ideas and modern insights into machine learning. Every chapter has been critically updated, and there are new chapters on key technologies. You'll be able to learn and work with TensorFlow more deeply than ever before, and get essential coverage of the Keras neural network library, along with the most recent updates to scikit-learn.
What you will learn
- Understand the key frameworks in data science, machine learning, and deep learning
- Harness the power of the latest Python open source libraries in machine learning
- Explore machine learning techniques using challenging real-world data
- Master deep neural network implementation using the TensorFlow library
- Learn the mechanics of classification algorithms to implement the best tool for the job
- Predict continuous target outcomes using regression analysis
- Uncover hidden patterns and structures in data with clustering
- Delve deeper into textual and social media data using sentiment analysis
Table of Contents
- Giving Computers the Ability to Learn from Data
- Training Simple Machine Learning Algorithms for Classification
- A Tour of Machine Learning Classifiers Using Scikit-Learn
- Building Good Training Sets - Data Preprocessing
- Compressing Data via Dimensionality Reduction
- Learning Best Practices for Model Evaluation and Hyperparameter Tuning
- Combining Different Models for Ensemble Learning
- Applying Machine Learning to Sentiment Analysis
- Embedding a Machine Learning Model into a Web Application
- Predicting Continuous Target Variables with Regression Analysis
- Working with Unlabeled Data - Clustering Analysis
- Implementing a Multilayer Artificial Neural Network from Scratch
- Parallelizing Neural Network Training with TensorFlow
- Going Deeper - The Mechanics of TensorFlow
- Classifying Images with Deep Convolutional Neural Networks
- Modeling Sequential Data using Recurrent Neural Networks
|AIQ: How People and Machines Are Smarter Together
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List price: $26.99
Author: Nick Polson
“There comes a time in the life of a subject when someone steps up and writes the book about it. AIQ explores the fascinating history of the ideas that drive this technology of the future and demystifies the core concepts behind it; the result is a positive and entertaining look at the great potential unlocked by marrying human creativity with powerful machines.” ―Steven D. Levitt, bestselling co-author of Freakonomics
From leading data scientists Nick Polson and James Scott, what everyone needs to know to understand how artificial intelligence is changing the world and how we can use this knowledge to make better decisions in our own lives.
Dozens of times per day, we all interact with intelligent machines that are constantly learning from the wealth of data now available to them. These machines, from smart phones to talking robots to self-driving cars, are remaking the world in the 21st century in the same way that the Industrial Revolution remade the world in the 19th century.
AIQ is based on a simple premise: if you want to understand the modern world, then you have to know a little bit of the mathematical language spoken by intelligent machines. AIQ will teach you that language―but in an unconventional way, anchored in stories rather than equations.
You will meet a fascinating cast of historical characters who have a lot to teach you about data, probability, and better thinking. Along the way, you'll see how these same ideas are playing out in the modern age of big data and intelligent machines―and how these technologies will soon help you to overcome some of your built-in cognitive weaknesses, giving you a chance to lead a happier, healthier, more fulfilled life.
|Human + Machine: Reimagining Work in the Age of AI
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List price: $32.00
Author: Paul R. Daugherty
AI is radically transforming business. Are you ready?
Look around you. Artificial intelligence is no longer just a futuristic notion. It's here right now--in software that senses what we need, supply chains that "think" in real time, and robots that respond to changes in their environment. Twenty-first-century pioneer companies are already using AI to innovate and grow fast. The bottom line is this: Businesses that understand how to harness AI can surge ahead. Those that neglect it will fall behind. Which side are you on?
In Human + Machine, Accenture leaders Paul R. Daugherty and H. James (Jim) Wilson show that the essence of the AI paradigm shift is the transformation of all business processes within an organization--whether related to breakthrough innovation, everyday customer service, or personal productivity habits. As humans and smart machines collaborate ever more closely, work processes become more fluid and adaptive, enabling companies to change them on the fly--or to completely reimagine them. AI is changing all the rules of how companies operate.
Based on the authors' experience and research with 1,500 organizations, the book reveals how companies are using the new rules of AI to leap ahead on innovation and profitability, as well as what you can do to achieve similar results. It describes six entirely new types of hybrid human + machine roles that every company must develop, and it includes a "leader’s guide" with the five crucial principles required to become an AI-fueled business.
Human + Machine provides the missing and much-needed management playbook for success in our new age of AI.
|Code: The Hidden Language of Computer Hardware and Software
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List price: $29.99
Author: Charles Petzold
Brand: Microsoft Press
What do flashlights, the British invasion, black cats, and seesaws have to do with computers? In CODE, they show us the ingenious ways we manipulate language and invent new means of communicating with each other. And through CODE, we see how this ingenuity and our very human compulsion to communicate have driven the technological innovations of the past two centuries.
Using everyday objects and familiar language systems such as Braille and Morse code, author Charles Petzold weaves an illuminating narrative for anyone who’s ever wondered about the secret inner life of computers and other smart machines.
It’s a cleverly illustrated and eminently comprehensible story—and along the way, you’ll discover you’ve gained a real context for understanding today’s world of PCs, digital media, and the Internet. No matter what your level of technical savvy, CODE will charm you—and perhaps even awaken the technophile within.
Charles Petzold's latest book, Code: The Hidden Language of Computer Hardware and Software, crosses over into general-interest nonfiction from his usual programming genre. It's a carefully written, carefully researched gem that will appeal to anyone who wants to understand computer technology at its essence. Readers learn about number systems (decimal, octal, binary, and all that) through Petzold's patient (and frequently entertaining) prose and then discover the logical systems that are used to process them. There's loads of historical information too. From Louis Braille's development of his eponymous raised-dot code to Intel Corporation's release of its early microprocessors, Petzold presents stories of people trying to communicate with (and by means of) mechanical and electrical devices. It's a fascinating progression of technologies, and Petzold presents a clear statement of how they fit together.
The real value of Code is in its explanation of technologies that have been obscured for years behind fancy user interfaces and programming environments, which, in the name of rapid application development, insulate the programmer from the machine. In a section on machine language, Petzold dissects the instruction sets of the genre-defining Intel 8080 and Motorola 6800 processors. He walks the reader through the process of performing various operations with each chip, explaining which opcodes poke which values into which registers along the way. Petzold knows that the hidden language of computers exhibits real beauty. In Code, he helps readers appreciate it. --David Wall
Topics covered: Mechanical and electrical representations of words and numbers, number systems, logic gates, performing mathematical operations with logic gates, microprocessors, machine code, memory and programming languages.
|The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World
Lowest new price: $12.40
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List price: $18.99
Author: Pedro Domingos
"Wonderfully erudite, humorous, and easy to read." --KDNuggets
In the world's top research labs and universities, the race is on to invent the ultimate learning algorithm: one capable of discovering any knowledge from data, and doing anything we want, before we even ask. In The Master Algorithm, Pedro Domingos lifts the veil to give us a peek inside the learning machines that power Google, Amazon, and your smartphone. He assembles a blueprint for the future universal learner--the Master Algorithm--and discusses what it will mean for business, science, and society. If data-ism is today's philosophy, this book is its bible.
|Pattern Recognition and Machine Learning (Information Science and Statistics)
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List price: $94.95
Author: Christopher M. Bishop
This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It uses graphical models to describe probability distributions when no other books apply graphical models to machine learning. No previous knowledge of pattern recognition or machine learning concepts is assumed. Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.
|Blockchain Basics: A Non-Technical Introduction in 25 Steps
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Author: Daniel Drescher
In 25 concise steps, you will learn the basics of blockchain technology. No mathematical formulas, program code, or computer science jargon are used. No previous knowledge in computer science, mathematics, programming, or cryptography is required. Terminology is explained through pictures, analogies, and metaphors.
This book bridges the gap that exists between purely technical books about the blockchain and purely business-focused books. It does so by explaining both the technical concepts that make up the blockchain and their role in business-relevant applications.
What You'll Learn
- What the blockchain is
- Why it is needed and what problem it solves
- Why there is so much excitement about the blockchain and its potential
- Major components and their purpose
- How various components of the blockchain work and interact
- Limitations, why they exist, and what has been done to overcome them
- Major application scenarios
Who This Book Is For
Everyone who wants to get a general idea of what blockchain technology is, how it works, and how it will potentially change the financial system as we know it
- Blockchain Technology Explained: The Ultimate Beginner’s Guide About Blockchain Wallet, Mining, Bitcoin, Ethereum, Litecoin, Zcash, Monero, Ripple, Dash, IOTA And Smart Contracts
- The Truth Machine: The Blockchain and the Future of Everything
- Building Blockchain Projects: Building decentralized Blockchain applications with Ethereum and Solidity
- Mastering Bitcoin: Programming the Open Blockchain
- Blockchain: Discover the Technology behind Smart Contracts, Wallets, Mining and Cryptocurrency (including Bitcoin, Ethereum, Ripple, Digibyte and Others)
- Blockchain For Dummies (For Dummies (Computers))
- Blockchain Revolution: How the Technology Behind Bitcoin Is Changing Money, Business, and the World
- Blockchain: Ultimate Beginner's Guide to Blockchain Technology - Cryptocurrency, Smart Contracts, Distributed Ledger, Fintech and Decentralized Applications
- The Business Blockchain: Promise, Practice, and Application of the Next Internet Technology
- Blockchain and the Law: The Rule of Code
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