Download or read book Machine Learning Control A Complete Guide 2020 Edition written by Gerardus Blokdyk and published by 5starcooks. This book was released on 2020-01-23 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: How can you become the company that would put you out of business? What controls do you have in place to protect data? What sources do you use to gather information for a Machine learning control study? What is the smallest subset of the problem you can usefully solve? What management system can you use to leverage the Machine learning control experience, ideas, and concerns of the people closest to the work to be done? Defining, designing, creating, and implementing a process to solve a challenge or meet an objective is the most valuable role... In EVERY group, company, organization and department. Unless you are talking a one-time, single-use project, there should be a process. Whether that process is managed and implemented by humans, AI, or a combination of the two, it needs to be designed by someone with a complex enough perspective to ask the right questions. Someone capable of asking the right questions and step back and say, 'What are we really trying to accomplish here? And is there a different way to look at it?' This Self-Assessment empowers people to do just that - whether their title is entrepreneur, manager, consultant, (Vice-)President, CxO etc... - they are the people who rule the future. They are the person who asks the right questions to make Machine Learning Control investments work better. This Machine Learning Control All-Inclusive Self-Assessment enables You to be that person. All the tools you need to an in-depth Machine Learning Control Self-Assessment. Featuring 942 new and updated case-based questions, organized into seven core areas of process design, this Self-Assessment will help you identify areas in which Machine Learning Control improvements can be made. In using the questions you will be better able to: - diagnose Machine Learning Control projects, initiatives, organizations, businesses and processes using accepted diagnostic standards and practices - implement evidence-based best practice strategies aligned with overall goals - integrate recent advances in Machine Learning Control and process design strategies into practice according to best practice guidelines Using a Self-Assessment tool known as the Machine Learning Control Scorecard, you will develop a clear picture of which Machine Learning Control areas need attention. Your purchase includes access details to the Machine Learning Control self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows your organization exactly what to do next. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation - In-depth and specific Machine Learning Control Checklists - Project management checklists and templates to assist with implementation INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.

Download or read book Machine Learning written by Steven Alex and published by . This book was released on 2019-11-06 with total page 135 pages. Available in PDF, EPUB and Kindle. Book excerpt: ★ ★ Buy the Paperback Version of this Book and Get the Kindle Book version for FREE ★ ★ Machine Learning (Update Edition 2019-2020) this Guide is a branch of artificial intelligence, This Machine Learning Series idea is relatively new. A science that researches machines to acquire new knowledge and new skills and to identify existing knowledge. The best way to understand the potential of machine learning is to explore how people and companies are currently taking advantage of it.If you are one of the almost 400 million people with machine learning worldwide, This book offers a method to Techniques! Not every machine learning model uses the same techniques, so training will depend on your approach. Let's consider a few examples: Psychology of learning Machine learning in practice Reinforcement learning Types of machine learning Learning by reinforcement Types of reinforcement The different types of learning This guidebook is going to take some time to explore machine learning, and what it is all about. There are so many different aspects of machine learning and how to make it work for your needs, and all of it is found in this guidebook. Some of the different topics that you will be able to learn about inside include: Neural networks Historical background Why use neural networks? Tasks of neural networks Deep learning Algorithms Starting with python Basic types of data Get access to free software and data sets so you can try out your very own machine learning software. See how advanced machine learning will impact our world in the future! Scroll Up and Click the Buy Now Button!

Download or read book A Human s Guide to Machine Intelligence written by Kartik Hosanagar and published by Penguin. This book was released on 2020-03-10 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Wharton professor and tech entrepreneur examines how algorithms and artificial intelligence are starting to run every aspect of our lives, and how we can shape the way they impact us Through the technology embedded in almost every major tech platform and every web-enabled device, algorithms and the artificial intelligence that underlies them make a staggering number of everyday decisions for us, from what products we buy, to where we decide to eat, to how we consume our news, to whom we date, and how we find a job. We've even delegated life-and-death decisions to algorithms--decisions once made by doctors, pilots, and judges. In his new book, Kartik Hosanagar surveys the brave new world of algorithmic decision-making and reveals the potentially dangerous biases they can give rise to as they increasingly run our lives. He makes the compelling case that we need to arm ourselves with a better, deeper, more nuanced understanding of the phenomenon of algorithmic thinking. And he gives us a route in, pointing out that algorithms often think a lot like their creators--that is, like you and me. Hosanagar draws on his experiences designing algorithms professionally--as well as on history, computer science, and psychology--to explore how algorithms work and why they occasionally go rogue, what drives our trust in them, and the many ramifications of algorithmic decision-making. He examines episodes like Microsoft's chatbot Tay, which was designed to converse on social media like a teenage girl, but instead turned sexist and racist; the fatal accidents of self-driving cars; and even our own common, and often frustrating, experiences on services like Netflix and Amazon. A Human's Guide to Machine Intelligence is an entertaining and provocative look at one of the most important developments of our time and a practical user's guide to this first wave of practical artificial intelligence.

Download or read book Machine Learning in Finance written by Matthew F. Dixon and published by Springer Nature. This book was released on 2020-07-01 with total page 565 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces machine learning methods in finance. It presents a unified treatment of machine learning and various statistical and computational disciplines in quantitative finance, such as financial econometrics and discrete time stochastic control, with an emphasis on how theory and hypothesis tests inform the choice of algorithm for financial data modeling and decision making. With the trend towards increasing computational resources and larger datasets, machine learning has grown into an important skillset for the finance industry. This book is written for advanced graduate students and academics in financial econometrics, mathematical finance and applied statistics, in addition to quants and data scientists in the field of quantitative finance. Machine Learning in Finance: From Theory to Practice is divided into three parts, each part covering theory and applications. The first presents supervised learning for cross-sectional data from both a Bayesian and frequentist perspective. The more advanced material places a firm emphasis on neural networks, including deep learning, as well as Gaussian processes, with examples in investment management and derivative modeling. The second part presents supervised learning for time series data, arguably the most common data type used in finance with examples in trading, stochastic volatility and fixed income modeling. Finally, the third part presents reinforcement learning and its applications in trading, investment and wealth management. Python code examples are provided to support the readers' understanding of the methodologies and applications. The book also includes more than 80 mathematical and programming exercises, with worked solutions available to instructors. As a bridge to research in this emergent field, the final chapter presents the frontiers of machine learning in finance from a researcher's perspective, highlighting how many well-known concepts in statistical physics are likely to emerge as important methodologies for machine learning in finance.

Download or read book Automated Machine Learning A Complete Guide 2020 Edition written by Gerardus Blokdyk and published by 5starcooks. This book was released on 2020-01-28 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: How are consistent Automated machine learning definitions important? Are there recognized Automated machine learning problems? Who is gathering information? What other organizational variables, such as reward systems or communication systems, affect the performance of this Automated machine learning process? Instead of going to current contacts for new ideas, what if you reconnected with dormant contacts--the people you used to know? If you were going reactivate a dormant tie, who would it be? Defining, designing, creating, and implementing a process to solve a challenge or meet an objective is the most valuable role... In EVERY group, company, organization and department. Unless you are talking a one-time, single-use project, there should be a process. Whether that process is managed and implemented by humans, AI, or a combination of the two, it needs to be designed by someone with a complex enough perspective to ask the right questions. Someone capable of asking the right questions and step back and say, 'What are we really trying to accomplish here? And is there a different way to look at it?' This Self-Assessment empowers people to do just that - whether their title is entrepreneur, manager, consultant, (Vice-)President, CxO etc... - they are the people who rule the future. They are the person who asks the right questions to make Automated Machine Learning investments work better. This Automated Machine Learning All-Inclusive Self-Assessment enables You to be that person. All the tools you need to an in-depth Automated Machine Learning Self-Assessment. Featuring 942 new and updated case-based questions, organized into seven core areas of process design, this Self-Assessment will help you identify areas in which Automated Machine Learning improvements can be made. In using the questions you will be better able to: - diagnose Automated Machine Learning projects, initiatives, organizations, businesses and processes using accepted diagnostic standards and practices - implement evidence-based best practice strategies aligned with overall goals - integrate recent advances in Automated Machine Learning and process design strategies into practice according to best practice guidelines Using a Self-Assessment tool known as the Automated Machine Learning Scorecard, you will develop a clear picture of which Automated Machine Learning areas need attention. Your purchase includes access details to the Automated Machine Learning self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows your organization exactly what to do next. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation - In-depth and specific Automated Machine Learning Checklists - Project management checklists and templates to assist with implementation INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.

Download or read book Supervised Machine Learning A Complete Guide 2020 Edition written by Gerardus Blokdyk and published by 5starcooks. This book was released on 2020-02-16 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: How is Supervised machine learning data gathered? What relationships among Supervised machine learning trends do you perceive? What Supervised machine learning data do you gather or use now? What are your most important goals for the strategic Supervised machine learning objectives? Is Supervised machine learning documentation maintained? This instant Supervised Machine Learning self-assessment will make you the accepted Supervised Machine Learning domain auditor by revealing just what you need to know to be fluent and ready for any Supervised Machine Learning challenge. How do I reduce the effort in the Supervised Machine Learning work to be done to get problems solved? How can I ensure that plans of action include every Supervised Machine Learning task and that every Supervised Machine Learning outcome is in place? How will I save time investigating strategic and tactical options and ensuring Supervised Machine Learning costs are low? How can I deliver tailored Supervised Machine Learning advice instantly with structured going-forward plans? There's no better guide through these mind-expanding questions than acclaimed best-selling author Gerard Blokdyk. Blokdyk ensures all Supervised Machine Learning essentials are covered, from every angle: the Supervised Machine Learning self-assessment shows succinctly and clearly that what needs to be clarified to organize the required activities and processes so that Supervised Machine Learning outcomes are achieved. Contains extensive criteria grounded in past and current successful projects and activities by experienced Supervised Machine Learning practitioners. Their mastery, combined with the easy elegance of the self-assessment, provides its superior value to you in knowing how to ensure the outcome of any efforts in Supervised Machine Learning are maximized with professional results. Your purchase includes access details to the Supervised Machine Learning self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows you exactly what to do next. Your exclusive instant access details can be found in your book. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation - In-depth and specific Supervised Machine Learning Checklists - Project management checklists and templates to assist with implementation INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.

Download or read book Linear Algebra and Optimization for Machine Learning written by Charu C. Aggarwal and published by Springer Nature. This book was released on 2020-05-13 with total page 507 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook introduces linear algebra and optimization in the context of machine learning. Examples and exercises are provided throughout the book. A solution manual for the exercises at the end of each chapter is available to teaching instructors. This textbook targets graduate level students and professors in computer science, mathematics and data science. Advanced undergraduate students can also use this textbook. The chapters for this textbook are organized as follows: 1. Linear algebra and its applications: The chapters focus on the basics of linear algebra together with their common applications to singular value decomposition, matrix factorization, similarity matrices (kernel methods), and graph analysis. Numerous machine learning applications have been used as examples, such as spectral clustering, kernel-based classification, and outlier detection. The tight integration of linear algebra methods with examples from machine learning differentiates this book from generic volumes on linear algebra. The focus is clearly on the most relevant aspects of linear algebra for machine learning and to teach readers how to apply these concepts. 2. Optimization and its applications: Much of machine learning is posed as an optimization problem in which we try to maximize the accuracy of regression and classification models. The “parent problem” of optimization-centric machine learning is least-squares regression. Interestingly, this problem arises in both linear algebra and optimization, and is one of the key connecting problems of the two fields. Least-squares regression is also the starting point for support vector machines, logistic regression, and recommender systems. Furthermore, the methods for dimensionality reduction and matrix factorization also require the development of optimization methods. A general view of optimization in computational graphs is discussed together with its applications to back propagation in neural networks. A frequent challenge faced by beginners in machine learning is the extensive background required in linear algebra and optimization. One problem is that the existing linear algebra and optimization courses are not specific to machine learning; therefore, one would typically have to complete more course material than is necessary to pick up machine learning. Furthermore, certain types of ideas and tricks from optimization and linear algebra recur more frequently in machine learning than other application-centric settings. Therefore, there is significant value in developing a view of linear algebra and optimization that is better suited to the specific perspective of machine learning.

Download or read book Artificial Intelligence By Example written by Denis Rothman and published by Packt Publishing Ltd. This book was released on 2020-02-28 with total page 579 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understand the fundamentals and develop your own AI solutions in this updated edition packed with many new examples Key FeaturesAI-based examples to guide you in designing and implementing machine intelligenceBuild machine intelligence from scratch using artificial intelligence examplesDevelop machine intelligence from scratch using real artificial intelligenceBook Description AI has the potential to replicate humans in every field. Artificial Intelligence By Example, Second Edition serves as a starting point for you to understand how AI is built, with the help of intriguing and exciting examples. This book will make you an adaptive thinker and help you apply concepts to real-world scenarios. Using some of the most interesting AI examples, right from computer programs such as a simple chess engine to cognitive chatbots, you will learn how to tackle the machine you are competing with. You will study some of the most advanced machine learning models, understand how to apply AI to blockchain and Internet of Things (IoT), and develop emotional quotient in chatbots using neural networks such as recurrent neural networks (RNNs) and convolutional neural networks (CNNs). This edition also has new examples for hybrid neural networks, combining reinforcement learning (RL) and deep learning (DL), chained algorithms, combining unsupervised learning with decision trees, random forests, combining DL and genetic algorithms, conversational user interfaces (CUI) for chatbots, neuromorphic computing, and quantum computing. By the end of this book, you will understand the fundamentals of AI and have worked through a number of examples that will help you develop your AI solutions. What you will learnApply k-nearest neighbors (KNN) to language translations and explore the opportunities in Google TranslateUnderstand chained algorithms combining unsupervised learning with decision treesSolve the XOR problem with feedforward neural networks (FNN) and build its architecture to represent a data flow graphLearn about meta learning models with hybrid neural networksCreate a chatbot and optimize its emotional intelligence deficiencies with tools such as Small Talk and data loggingBuilding conversational user interfaces (CUI) for chatbotsWriting genetic algorithms that optimize deep learning neural networksBuild quantum computing circuitsWho this book is for Developers and those interested in AI, who want to understand the fundamentals of Artificial Intelligence and implement them practically. Prior experience with Python programming and statistical knowledge is essential to make the most out of this book.

Download or read book Adaptive Machine Learning A Complete Guide 2020 Edition written by Gerardus Blokdyk and published by 5starcooks. This book was released on 2020-05-08 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: How will you measure the results? Is there any additional Adaptive machine learning definition of success? What is out-of-scope initially? What are the estimated costs of proposed changes? What are you trying to prove to yourself, and how might it be hijacking your life and business success? Defining, designing, creating, and implementing a process to solve a challenge or meet an objective is the most valuable role... In EVERY group, company, organization and department. Unless you are talking a one-time, single-use project, there should be a process. Whether that process is managed and implemented by humans, AI, or a combination of the two, it needs to be designed by someone with a complex enough perspective to ask the right questions. Someone capable of asking the right questions and step back and say, 'What are we really trying to accomplish here? And is there a different way to look at it?' This Self-Assessment empowers people to do just that - whether their title is entrepreneur, manager, consultant, (Vice-)President, CxO etc... - they are the people who rule the future. They are the person who asks the right questions to make Adaptive Machine Learning investments work better. This Adaptive Machine Learning All-Inclusive Self-Assessment enables You to be that person. All the tools you need to an in-depth Adaptive Machine Learning Self-Assessment. Featuring 951 new and updated case-based questions, organized into seven core areas of process design, this Self-Assessment will help you identify areas in which Adaptive Machine Learning improvements can be made. In using the questions you will be better able to: - diagnose Adaptive Machine Learning projects, initiatives, organizations, businesses and processes using accepted diagnostic standards and practices - implement evidence-based best practice strategies aligned with overall goals - integrate recent advances in Adaptive Machine Learning and process design strategies into practice according to best practice guidelines Using a Self-Assessment tool known as the Adaptive Machine Learning Scorecard, you will develop a clear picture of which Adaptive Machine Learning areas need attention. Your purchase includes access details to the Adaptive Machine Learning self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows your organization exactly what to do next. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation - In-depth and specific Adaptive Machine Learning Checklists - Project management checklists and templates to assist with implementation INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.

Download or read book Machine Learning a Complete Guide 2019 Edition written by Gerardus Blokdyk and published by 5starcooks. This book was released on 2018-12-21 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: What is the current state of the data? What is the relationship between different learning algorithms, and which should be used when? Can you use cloud-based data to train machine learning models? What rights should artificial beings have? How does knowledge lead to action? This powerful Machine Learning self-assessment will make you the credible Machine Learning domain auditor by revealing just what you need to know to be fluent and ready for any Machine Learning challenge. How do I reduce the effort in the Machine Learning work to be done to get problems solved? How can I ensure that plans of action include every Machine Learning task and that every Machine Learning outcome is in place? How will I save time investigating strategic and tactical options and ensuring Machine Learning costs are low? How can I deliver tailored Machine Learning advice instantly with structured going-forward plans? There's no better guide through these mind-expanding questions than acclaimed best-selling author Gerard Blokdyk. Blokdyk ensures all Machine Learning essentials are covered, from every angle: the Machine Learning self-assessment shows succinctly and clearly that what needs to be clarified to organize the required activities and processes so that Machine Learning outcomes are achieved. Contains extensive criteria grounded in past and current successful projects and activities by experienced Machine Learning practitioners. Their mastery, combined with the easy elegance of the self-assessment, provides its superior value to you in knowing how to ensure the outcome of any efforts in Machine Learning are maximized with professional results. Your purchase includes access details to the Machine Learning self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows you exactly what to do next. Your exclusive instant access details can be found in your book. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation - In-depth and specific Machine Learning Checklists - Project management checklists and templates to assist with implementation INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.

Download or read book Reinforcement Learning second edition written by Richard S. Sutton and published by MIT Press. This book was released on 2018-11-13 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics. Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning.

Download or read book MATLAB Machine Learning written by Michael Paluszek and published by Apress. This book was released on 2016-12-28 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a comprehensive guide to machine learning with worked examples in MATLAB. It starts with an overview of the history of Artificial Intelligence and automatic control and how the field of machine learning grew from these. It provides descriptions of all major areas in machine learning. The book reviews commercially available packages for machine learning and shows how they fit into the field. The book then shows how MATLAB can be used to solve machine learning problems and how MATLAB graphics can enhance the programmer’s understanding of the results and help users of their software grasp the results. Machine Learning can be very mathematical. The mathematics for each area is introduced in a clear and concise form so that even casual readers can understand the math. Readers from all areas of engineering will see connections to what they know and will learn new technology. The book then provides complete solutions in MATLAB for several important problems in machine learning including face identification, autonomous driving, and data classification. Full source code is provided for all of the examples and applications in the book. What you'll learn: An overview of the field of machine learning Commercial and open source packages in MATLAB How to use MATLAB for programming and building machine learning applications MATLAB graphics for machine learning Practical real world examples in MATLAB for major applications of machine learning in big data Who is this book for: The primary audiences are engineers and engineering students wanting a comprehensive and practical introduction to machine learning.

Download or read book Machine Learning written by Mike Cowley and published by Independently Published. This book was released on 2019-10-31 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: Are you completely new to the world of programming, and wondering if a path in machine learning is for you? Are you already a programmer in other fields, but you are intrigued by the possibilities the world of machine learning has to offer? If you answered yes to any of the questions above, then this guide is for you. In this guide, Mike Cowley demystifies the world of machine learning and shows you what you need to do to become an expert in this field. Mike helps you get rid of information overload by providing clarity, helping you take the first steps into the exciting world of machine learning. Among the insights contained in this guide, you're going to discover: Everything you need to know about Machine Learning as a beginner: What it really is, Its history, how it works and what the future looks like for ML practitioners (Hint: It's bright!) What you'll need to get started with machine learning as a beginner The machine learning toolbox you need if you want to become an effective programmer Myths about machine learning and artificial intelligence that widely popular but completely wrong How to effectively use machine learning to get rid of bottle-necks in high-impact industries The 7 types of machine learning used in modern computing The subtle, but important difference between machine learning and artificial intelligence ...and tons more! Whether you're new to the world of programming or you're an experienced machine learning practitioner with years under your belt, this guide contains everything you'll need--from information and use cases--to help you develop your skills and take your projects to the next level. Scroll up and click the "add to cart" button now to master the art of machine learning!

Download or read book Machine Learning A Complete Guide to Machine Learning for Beginners Includes Algorithms Analysis Data Mining and Artificial Intellig written by ML & Ai Academy and published by ML and AI Academy. This book was released on 2021-03-20 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: !! 55% OFF for Bookstores!! NOW at 27.95 instead of 37.95 !! Buy it NOW and let your customers get addicted to this awesome book!

Download or read book The Alignment Problem Machine Learning and Human Values written by Brian Christian and published by W. W. Norton & Company. This book was released on 2020-10-06 with total page 459 pages. Available in PDF, EPUB and Kindle. Book excerpt: A jaw-dropping exploration of everything that goes wrong when we build AI systems and the movement to fix them. Today’s “machine-learning” systems, trained by data, are so effective that we’ve invited them to see and hear for us—and to make decisions on our behalf. But alarm bells are ringing. Recent years have seen an eruption of concern as the field of machine learning advances. When the systems we attempt to teach will not, in the end, do what we want or what we expect, ethical and potentially existential risks emerge. Researchers call this the alignment problem. Systems cull résumés until, years later, we discover that they have inherent gender biases. Algorithms decide bail and parole—and appear to assess Black and White defendants differently. We can no longer assume that our mortgage application, or even our medical tests, will be seen by human eyes. And as autonomous vehicles share our streets, we are increasingly putting our lives in their hands. The mathematical and computational models driving these changes range in complexity from something that can fit on a spreadsheet to a complex system that might credibly be called “artificial intelligence.” They are steadily replacing both human judgment and explicitly programmed software. In best-selling author Brian Christian’s riveting account, we meet the alignment problem’s “first-responders,” and learn their ambitious plan to solve it before our hands are completely off the wheel. In a masterful blend of history and on-the ground reporting, Christian traces the explosive growth in the field of machine learning and surveys its current, sprawling frontier. Readers encounter a discipline finding its legs amid exhilarating and sometimes terrifying progress. Whether they—and we—succeed or fail in solving the alignment problem will be a defining human story. The Alignment Problem offers an unflinching reckoning with humanity’s biases and blind spots, our own unstated assumptions and often contradictory goals. A dazzlingly interdisciplinary work, it takes a hard look not only at our technology but at our culture—and finds a story by turns harrowing and hopeful.

Download or read book Machine Control A Complete Guide 2020 Edition written by Gerardus Blokdyk and published by 5starcooks. This book was released on 2020-03 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you were responsible for initiating and implementing major changes in your organization, what steps might you take to ensure acceptance of those changes? What are the best opportunities for value improvement? Do you have any cost Machine control limitation requirements? Are you aware of what could cause a problem? What needs improvement? Why? This one-of-a-kind Machine Control self-assessment will make you the trusted Machine Control domain standout by revealing just what you need to know to be fluent and ready for any Machine Control challenge. How do I reduce the effort in the Machine Control work to be done to get problems solved? How can I ensure that plans of action include every Machine Control task and that every Machine Control outcome is in place? How will I save time investigating strategic and tactical options and ensuring Machine Control costs are low? How can I deliver tailored Machine Control advice instantly with structured going-forward plans? There's no better guide through these mind-expanding questions than acclaimed best-selling author Gerard Blokdyk. Blokdyk ensures all Machine Control essentials are covered, from every angle: the Machine Control self-assessment shows succinctly and clearly that what needs to be clarified to organize the required activities and processes so that Machine Control outcomes are achieved. Contains extensive criteria grounded in past and current successful projects and activities by experienced Machine Control practitioners. Their mastery, combined with the easy elegance of the self-assessment, provides its superior value to you in knowing how to ensure the outcome of any efforts in Machine Control are maximized with professional results. Your purchase includes access details to the Machine Control self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows you exactly what to do next. Your exclusive instant access details can be found in your book. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation - In-depth and specific Machine Control Checklists - Project management checklists and templates to assist with implementation INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.

Download or read book Master Machine Learning written by Denis Sanchez Leyva and published by Independently Published. This book was released on 2024-06-19 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Master Machine Learning: Complete Guide for Beginners" is a comprehensive and practical guide designed to take you from basic concepts to the implementation of advanced Machine Learning models. This book is structured to provide a complete and applicable understanding of the field, covering everything from data preparation to model deployment in web and mobile applications. Each chapter includes detailed explanations, practical examples, and projects that will help you consolidate your knowledge and develop essential skills in Machine Learning. Additionally, we explore emerging trends and recent advances, ensuring you stay up-to-date with the latest innovations in the field. Whether you are a student, developer, researcher, or business professional, this book will equip you with the tools and knowledge necessary to apply Machine Learning techniques to your projects and advance your career.