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Author: Steve Miller
Publisher: Sound Wisdom
ISBN: 1640951717
Category : Business & Economics
Languages : en
Pages : 112
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Book Description
What separates average businesses from extraordinarily successful ones? Better product? Nope. Your competitor will rapidly reverse-engineer your "secret sauce" and get their "better-than-you" version on the market faster than you can say "Usain Bolt." Better customer service? Guess what? All of your competitors say they provide the best customer service. It's a wishy washy phrase ... a vague generality with no meaningful specific. Better pricing? You're kidding, right? The company that lives on price dies on price. Harsher reality: Almost all industries today struggle with the increasing commoditization of their products and services, putting considerable pressure on prices and margins, leading to fiercer competition. The Solution? You must create an Uncopyable Attachment with your customers. They must see you as not only delivering a superior product but also as a high-value relationship they simply cannot get anywhere else. In Uncopyable, Steve Miller compellingly argues that new advantage isn't found by going "outside the box" - you must actually build your own box. Uncopyable will guide you to achieving an unfair and enduring competitive advantage.
Author: Steve Miller
Publisher: Sound Wisdom
ISBN: 1640951717
Category : Business & Economics
Languages : en
Pages : 112
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Book Description
What separates average businesses from extraordinarily successful ones? Better product? Nope. Your competitor will rapidly reverse-engineer your "secret sauce" and get their "better-than-you" version on the market faster than you can say "Usain Bolt." Better customer service? Guess what? All of your competitors say they provide the best customer service. It's a wishy washy phrase ... a vague generality with no meaningful specific. Better pricing? You're kidding, right? The company that lives on price dies on price. Harsher reality: Almost all industries today struggle with the increasing commoditization of their products and services, putting considerable pressure on prices and margins, leading to fiercer competition. The Solution? You must create an Uncopyable Attachment with your customers. They must see you as not only delivering a superior product but also as a high-value relationship they simply cannot get anywhere else. In Uncopyable, Steve Miller compellingly argues that new advantage isn't found by going "outside the box" - you must actually build your own box. Uncopyable will guide you to achieving an unfair and enduring competitive advantage.
Author: Scott Meyers
Publisher: Pearson Education
ISBN: 0132702061
Category : Computers
Languages : en
Pages : 320
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Book Description
“Every C++ professional needs a copy of Effective C++. It is an absolute must-read for anyone thinking of doing serious C++ development. If you’ve never read Effective C++ and you think you know everything about C++, think again.” — Steve Schirripa, Software Engineer, Google “C++ and the C++ community have grown up in the last fifteen years, and the third edition of Effective C++ reflects this. The clear and precise style of the book is evidence of Scott’s deep insight and distinctive ability to impart knowledge.” — Gerhard Kreuzer, Research and Development Engineer, Siemens AG The first two editions of Effective C++ were embraced by hundreds of thousands of programmers worldwide. The reason is clear: Scott Meyers’ practical approach to C++ describes the rules of thumb used by the experts — the things they almost always do or almost always avoid doing — to produce clear, correct, efficient code. The book is organized around 55 specific guidelines, each of which describes a way to write better C++. Each is backed by concrete examples. For this third edition, more than half the content is new, including added chapters on managing resources and using templates. Topics from the second edition have been extensively revised to reflect modern design considerations, including exceptions, design patterns, and multithreading. Important features of Effective C++ include: Expert guidance on the design of effective classes, functions, templates, and inheritance hierarchies. Applications of new “TR1” standard library functionality, along with comparisons to existing standard library components. Insights into differences between C++ and other languages (e.g., Java, C#, C) that help developers from those languages assimilate “the C++ way” of doing things.
Author: Kay Miller
Publisher: Sound Wisdom
ISBN: 1640953647
Category : Business & Economics
Languages : en
Pages : 162
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Book Description
Make more sales, grow your network, and become a top earner! Uncopyable Sales Secrets teaches a foolproof system for creating an Uncopyable Attachment with your prospects and clients so that you can fill your sales pipeline, close more deals, and build a loyal customer base. Sales success isn’t the result of being good at selling a product or service…it comes from being good at selling yourself. That’s right—you, not your product or service, are the most valuable asset to the customer. To become a master salesperson, you have to make the relationship with the buyer uniquely valuable. You have to make yourself invaluable and irreplaceable. In short, you have to make yourself and the partnership you’re pitching Uncopyable. Learn how to reach buyers before your competition—and become their personal and professional ally—in this breakthrough book on high-performance selling. Kay Miller, a powerhouse sales guru who began her career as one of the first women hired by an industry leader in hardware and went on to become the No. 1 muffler salesperson in the world, shares the proven principles responsible for her sales success. Kay calls it the Uncopyable Sales Strategy, and it involves: Creating a win-win outlook for both you and your customers Stepping beyond fear to consistently expand your comfort zone Getting in the door by making an Uncopyable first impression Trading negotiation and persuasion for mutually profitable relationship-building Leveraging multiple contact platforms to maximize communication effectiveness Securing the order by asking the right questions, listening, and following up And more! Uncopyable Sales Secrets equips you with the techniques you need to enhance your prospecting skills, make more sales, grow your network, and become a top earner in your organization. When you execute this process, your customers will see you not only as delivering a superior product or service, but also as part of a high-value relationship they simply cannot get anywhere else. Read this book…before your competition does!
Author: Michael Kanaan
Publisher: BenBella Books
ISBN: 1950665135
Category : Science
Languages : en
Pages : 249
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Book Description
Late in 2017, the global significance of the conversation about artificial intelligence (AI) changed forever. China put the world on alert when it released a plan to dominate all aspects of AI across the planet. Only weeks later, Vladimir Putin raised a Russian red flag in response by declaring AI the future for all humankind, and proclaiming that, "Whoever becomes the leader in this sphere will become the ruler of the world." The race was on. Consistent with their unique national agendas, countries throughout the world began plotting their paths and hurrying their pace. Now, not long after, the race has become a sprint. Despite everything at stake, to most of us AI remains shrouded by a cloud of mystery and misunderstanding. Hidden behind complicated and technical jargon and confused by fantastical depictions of science fiction, the modern realities of AI and its profound implications are hard to decipher, but crucial to recognize. In T-Minus AI: Humanity's Countdown to Artificial Intelligence and the New Pursuit of Global Power, author Michael Kanaan explains AI from a human-oriented perspective we can all finally understand. A recognized national expert and the U.S. Air Force's first Chairperson for Artificial Intelligence, Kanaan weaves a compelling new view on our history of innovation and technology to masterfully explain what each of us should know about modern computing, AI, and machine learning. Kanaan also dives into the global implications of AI by illuminating the cultural and national vulnerabilities already exposed and the pressing issues now squarely on the table. AI has already become China's all-purpose tool to impose its authoritarian influence around the world. Russia, playing catch up, is weaponizing AI through its military systems and now infamous, aggressive efforts to disrupt democracy by whatever disinformation means possible. America and like-minded nations are awakening to these new realities—and the paths they're electing to follow echo loudly the political foundations and, in most cases, the moral imperatives upon which they were formed. As we march toward a future far different than ever imagined, T-Minus AI is fascinating and crucially well-timed. It leaves the fiction behind, paints the alarming implications of AI for what they actually are, and calls for unified action to protect fundamental human rights and dignities for all.
Author: Rajesh R V
Publisher: Packt Publishing Ltd
ISBN: 1800568207
Category : Computers
Languages : en
Pages : 372
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Book Description
A guide to successfully operating in a lean-agile organization for solutions architects and enterprise architects Key FeaturesDevelop the right combination of processes and technical excellence to address architectural challengesExplore a range of architectural techniques to modernize legacy systemsDiscover how to design and continuously improve well-architected sustainable softwareBook Description Many organizations have embraced Agile methodologies to transform their ability to rapidly respond to constantly changing customer demands. However, in this melee, many enterprises often neglect to invest in architects by presuming architecture is not an intrinsic element of Agile software development. Since the role of an architect is not pre-defined in Agile, many organizations struggle to position architects, often resulting in friction with other roles or a failure to provide a clear learning path for architects to be productive. This book guides architects and organizations through new Agile ways of incrementally developing the architecture for delivering an uninterrupted, continuous flow of values that meets customer needs. You'll explore various aspects of Agile architecture and how it differs from traditional architecture. The book later covers Agile architects' responsibilities and how architects can add significant value by positioning themselves appropriately in the Agile flow of work. Through examples, you'll also learn concepts such as architectural decision backlog,the last responsible moment, value delivery, architecting for change, DevOps, and evolutionary collaboration. By the end of this Agile book, you'll be able to operate as an architect in Agile development initiatives and successfully architect reliable software systems. What you will learnAcquire clarity on the duties of architects in Agile developmentUnderstand architectural styles such as domain-driven design and microservicesIdentify the pitfalls of traditional architecture and learn how to develop solutionsUnderstand the principles of value and data-driven architectureDiscover DevOps and continuous delivery from an architect's perspectiveAdopt Lean-Agile documentation and governanceDevelop a set of personal and interpersonal qualitiesFind out how to lead the transformation to achieve organization-wide agilityWho this book is for This agile study guide is for architects currently working on agile development projects or aspiring to work on agile software delivery, irrespective of the methodology they are using. You will also find this book useful if you're a senior developer or a budding architect looking to understand an agile architect's role by embracing agile architecture strategies and a lean-agile mindset. To understand the concepts covered in this book easily, you need to have prior knowledge of basic agile development practices.
Author: Yuxi (Hayden) Liu
Publisher: Packt Publishing Ltd
ISBN: 1838553231
Category : Computers
Languages : en
Pages : 334
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Book Description
Implement reinforcement learning techniques and algorithms with the help of real-world examples and recipes Key FeaturesUse PyTorch 1.x to design and build self-learning artificial intelligence (AI) modelsImplement RL algorithms to solve control and optimization challenges faced by data scientists todayApply modern RL libraries to simulate a controlled environment for your projectsBook Description Reinforcement learning (RL) is a branch of machine learning that has gained popularity in recent times. It allows you to train AI models that learn from their own actions and optimize their behavior. PyTorch has also emerged as the preferred tool for training RL models because of its efficiency and ease of use. With this book, you'll explore the important RL concepts and the implementation of algorithms in PyTorch 1.x. The recipes in the book, along with real-world examples, will help you master various RL techniques, such as dynamic programming, Monte Carlo simulations, temporal difference, and Q-learning. You'll also gain insights into industry-specific applications of these techniques. Later chapters will guide you through solving problems such as the multi-armed bandit problem and the cartpole problem using the multi-armed bandit algorithm and function approximation. You'll also learn how to use Deep Q-Networks to complete Atari games, along with how to effectively implement policy gradients. Finally, you'll discover how RL techniques are applied to Blackjack, Gridworld environments, internet advertising, and the Flappy Bird game. By the end of this book, you'll have developed the skills you need to implement popular RL algorithms and use RL techniques to solve real-world problems. What you will learnUse Q-learning and the state–action–reward–state–action (SARSA) algorithm to solve various Gridworld problemsDevelop a multi-armed bandit algorithm to optimize display advertisingScale up learning and control processes using Deep Q-NetworksSimulate Markov Decision Processes, OpenAI Gym environments, and other common control problemsSelect and build RL models, evaluate their performance, and optimize and deploy themUse policy gradient methods to solve continuous RL problemsWho this book is for Machine learning engineers, data scientists and AI researchers looking for quick solutions to different reinforcement learning problems will find this book useful. Although prior knowledge of machine learning concepts is required, experience with PyTorch will be useful but not necessary.
Author: Sowmya Vajjala
Publisher: O'Reilly Media
ISBN: 149205402X
Category : Computers
Languages : en
Pages : 455
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Book Description
Many books and courses tackle natural language processing (NLP) problems with toy use cases and well-defined datasets. But if you want to build, iterate, and scale NLP systems in a business setting and tailor them for particular industry verticals, this is your guide. Software engineers and data scientists will learn how to navigate the maze of options available at each step of the journey. Through the course of the book, authors Sowmya Vajjala, Bodhisattwa Majumder, Anuj Gupta, and Harshit Surana will guide you through the process of building real-world NLP solutions embedded in larger product setups. You’ll learn how to adapt your solutions for different industry verticals such as healthcare, social media, and retail. With this book, you’ll: Understand the wide spectrum of problem statements, tasks, and solution approaches within NLP Implement and evaluate different NLP applications using machine learning and deep learning methods Fine-tune your NLP solution based on your business problem and industry vertical Evaluate various algorithms and approaches for NLP product tasks, datasets, and stages Produce software solutions following best practices around release, deployment, and DevOps for NLP systems Understand best practices, opportunities, and the roadmap for NLP from a business and product leader’s perspective
Author: Scott Meyers
Publisher: Addison-Wesley
ISBN: 0132979187
Category : Computers
Languages : en
Pages : 1045
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Book Description
Scott Meyers’s seminal C++ books– Effective C++ , More Effective C++ , and Effective STL –have been immensely helpful to hundreds of thousands of C++ programmers. All three are finally available together in this eBook collection. Effective C++ has been embraced by hundreds of thousands of programmers worldwide. The reason is clear: Scott Meyers’s practical approach to C++ describes the rules of thumb used by the experts to produce clear, correct, efficient code. The book is organized around 55 specific guidelines, each of which describes a way to write better C++. Each is backed by concrete examples. In More Effective C++, Meyers presents 35 ways to improve your programs and designs. Drawing on years of experience, Meyers explains how to write software that is more effective: more efficient, more robust, more consistent, more portable, and more reusable. In short, how to write C++ software that’s just plain better. In Effective STL, Meyers goes beyond describing what's in the STL to show you how to use it. Each of the book’s 50 guidelines is backed by Meyers’s legendary analysis and incisive examples, so you’ll learn not only what to do, but also when to do it–and why. Together in this collection, these books include the following important features: Expert guidance on the design of effective classes, functions, templates, and inheritance hierarchies. Applications of new “TR1” standard library functionality, along with comparisons to existing standard library components. Insights into differences between C++ and other languages (e.g., Java, C#, C) that help developers from those languages assimilate “the C++ way” of doing things. Proven methods for improving program efficiency, including incisive examinations of the time/space costs of C++ language features Comprehensive descriptions of advanced techniques used by C++ experts, including placement new, virtual constructors, smart pointers, reference counting, proxy classes, and double-dispatching Examples of the profound impact of exception handling on the structure and behavior of C++ classes and functions Practical treatments of new language features, including bool, mutable, explicit, namespaces, member templates, the Standard Template Library, and more. If your compilers don’t yet support these features, Meyers shows you how to get the job done without them. Advice on choosing among standard STL containers (like vector and list), nonstandard STL containers (like hash_set and hash_map), and non-STL containers (like bitset). Techniques to maximize the efficiency of the STL and the programs that use it. Insights into the behavior of iterators, function objects, and allocators, including things you should not do. Guidance for the proper use of algorithms and member functions whose names are the same (e.g., find), but whose actions differ in subtle (but important) ways. Discussions of potential portability problems, including straightforward ways to avoid them.
Author: Giuseppe Bonaccorso
Publisher: Packt Publishing Ltd
ISBN: 1788625900
Category : Computers
Languages : en
Pages : 567
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Book Description
Explore and master the most important algorithms for solving complex machine learning problems. Key Features Discover high-performing machine learning algorithms and understand how they work in depth. One-stop solution to mastering supervised, unsupervised, and semi-supervised machine learning algorithms and their implementation. Master concepts related to algorithm tuning, parameter optimization, and more Book Description Machine learning is a subset of AI that aims to make modern-day computer systems smarter and more intelligent. The real power of machine learning resides in its algorithms, which make even the most difficult things capable of being handled by machines. However, with the advancement in the technology and requirements of data, machines will have to be smarter than they are today to meet the overwhelming data needs; mastering these algorithms and using them optimally is the need of the hour. Mastering Machine Learning Algorithms is your complete guide to quickly getting to grips with popular machine learning algorithms. You will be introduced to the most widely used algorithms in supervised, unsupervised, and semi-supervised machine learning, and will learn how to use them in the best possible manner. Ranging from Bayesian models to the MCMC algorithm to Hidden Markov models, this book will teach you how to extract features from your dataset and perform dimensionality reduction by making use of Python-based libraries such as scikit-learn. You will also learn how to use Keras and TensorFlow to train effective neural networks. If you are looking for a single resource to study, implement, and solve end-to-end machine learning problems and use-cases, this is the book you need. What you will learn Explore how a ML model can be trained, optimized, and evaluated Understand how to create and learn static and dynamic probabilistic models Successfully cluster high-dimensional data and evaluate model accuracy Discover how artificial neural networks work and how to train, optimize, and validate them Work with Autoencoders and Generative Adversarial Networks Apply label spreading and propagation to large datasets Explore the most important Reinforcement Learning techniques Who this book is for This book is an ideal and relevant source of content for data science professionals who want to delve into complex machine learning algorithms, calibrate models, and improve the predictions of the trained model. A basic knowledge of machine learning is preferred to get the best out of this guide.
Author: Jay Dawani
Publisher: Packt Publishing Ltd
ISBN: 183864184X
Category : Computers
Languages : en
Pages : 347
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Book Description
A comprehensive guide to getting well-versed with the mathematical techniques for building modern deep learning architectures Key FeaturesUnderstand linear algebra, calculus, gradient algorithms, and other concepts essential for training deep neural networksLearn the mathematical concepts needed to understand how deep learning models functionUse deep learning for solving problems related to vision, image, text, and sequence applicationsBook Description Most programmers and data scientists struggle with mathematics, having either overlooked or forgotten core mathematical concepts. This book uses Python libraries to help you understand the math required to build deep learning (DL) models. You'll begin by learning about core mathematical and modern computational techniques used to design and implement DL algorithms. This book will cover essential topics, such as linear algebra, eigenvalues and eigenvectors, the singular value decomposition concept, and gradient algorithms, to help you understand how to train deep neural networks. Later chapters focus on important neural networks, such as the linear neural network and multilayer perceptrons, with a primary focus on helping you learn how each model works. As you advance, you will delve into the math used for regularization, multi-layered DL, forward propagation, optimization, and backpropagation techniques to understand what it takes to build full-fledged DL models. Finally, you’ll explore CNN, recurrent neural network (RNN), and GAN models and their application. By the end of this book, you'll have built a strong foundation in neural networks and DL mathematical concepts, which will help you to confidently research and build custom models in DL. What you will learnUnderstand the key mathematical concepts for building neural network modelsDiscover core multivariable calculus conceptsImprove the performance of deep learning models using optimization techniquesCover optimization algorithms, from basic stochastic gradient descent (SGD) to the advanced Adam optimizerUnderstand computational graphs and their importance in DLExplore the backpropagation algorithm to reduce output errorCover DL algorithms such as convolutional neural networks (CNNs), sequence models, and generative adversarial networks (GANs)Who this book is for This book is for data scientists, machine learning developers, aspiring deep learning developers, or anyone who wants to understand the foundation of deep learning by learning the math behind it. Working knowledge of the Python programming language and machine learning basics is required.
