Search Results - (((((((want OR hands) OR canton) OR makes) OR cantor) OR anne) OR shared) OR hints) algorithms.

A Hands-On Guide to Designing Embedded Systems. by Taylor, Adam

Table of Contents: “…-- 3.7 Finite State Machine Design -- 3.7.1 Defining a State Machine -- 3.7.2 Algorithmic State Diagrams -- 3.7.3 Moore or Mealy: What Should I Choose? …”
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Sharing economy and big data analytics by Sedkaoui, Soraya, Khelfaoui, Mounia

Table of Contents: “…The Sharing Economy or the Emergence of a New Business Model. …”
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Decision making : a psychophysics application of network science, Center for Nonlinear Science, University of North Texas, USA, 10-13 January 2010

Table of Contents: “…Overview of ARO program on network science for human decision making B.J. West; 1. Introduction; 2. Background; 2.1. …”
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Hands-On Reinforcement Learning with Python : Master Reinforcement and Deep Reinforcement Learning Using OpenAI Gym and TensorFlow. by Ravichandiran, Sudharsan

Table of Contents: “…Solving the taxi problem using Q learningSARSA; Solving the taxi problem using SARSA; The difference between Q learning and SARSA; Summary; Questions; Further reading; Chapter 6: Multi-Armed Bandit Problem; The MAB problem; The epsilon-greedy policy; The softmax exploration algorithm; The upper confidence bound algorithm; The Thompson sampling algorithm; Applications of MAB; Identifying the right advertisement banner using MAB; Contextual bandits; Summary; Questions; Further reading; Chapter 7: Deep Learning Fundamentals; Artificial neurons; ANNs; Input layer; Hidden layer; Output layer.…”
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Hands-on ensemble learning with Python : build highly optimized ensemble machine learning models using scikit-learn and Keras by Kyriakides, George, Margaritis, Konstantinos G.

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Hands-On Artificial Intelligence for IoT : Expert Machine Learning and Deep Learning Techniques for Developing Smarter IoT Systems. by Kapoor, Amita

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Hands-On Automated Machine Learning : a beginner's guide to building automated machine learning systems using AutoML and Python. by Das, Sibanjan

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Hands-on artificial intelligence for cybersecurity : implement smart AI systems for preventing cyber attacks and detecting threats and network anomalies by Parisi, Alessandro

Table of Contents: “…; Useful keyboard shortcuts; Choose your notebook kernel; Getting your hands dirty; Installing DL libraries; Deep learning pros and cons for cybersecurity; TensorFlow; Keras…”
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Hands-on recommendation systems with Python : start building powerful and personalized, recommendation engines with Python by Banik, Rounak

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Hands-on penetration testing on Windows : unleash Kali Linux, PowerShell, and Windows debugging tools for security testing and analysis by Bramwell, Phil

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Uberland : how algorithms are rewriting the rules of work by Rosenblat, Alex, 1987-

Table of Contents: “…Introduction : using an app to go to work-Uber as a symbol of the new economy -- Workers as digital pawns : how Uber uses the sharing economy to exploit everyone -- Motivations to drive : how Uber creates jobs for many at the expense of a few -- Grandiose promises : how Uber proposes entrepreneurship to the masses -- The shady middleman : how Uber plays broker to line its pockets -- Behind the curtain : how Uber rules drivers with algorithms -- In the big leagues : how Uber plays ball -- Conclusion : the new age of Uber-how technology consumption rewrote the rules of work -- Appendix 1. methodology : how I studied Uber -- Appendix 2. ridehailing beyond Uber : meet Lyft, the younger twin.…”
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The discrete fourier transform : theory, algorithms and applications by Sundararajan, D.

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Self-learning and adaptive algorithms for business applications : a guide to adaptive neuro-fuzzy systems for fuzzy clustering under uncertainty conditions by Hu, Zhengbing, Bodyanskiy, Yevgeniy V., Tyshchenko, Oleksii

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Engineering an Algorithm for Reducing Variation in Manufacturing Processes. by Steiner, Stefan H.

Table of Contents: “…Material on Enclosed CD-ROM; Figures and Tables; Acknowledgments; Preface; 1 Introduction; PART I Setting the Stage; 2 Describing Processes; 3 Seven Approaches to Variation Reduction; 4 An Algorithm for Reducing Variation; 5 Obtaining Process Knowledge Empirically; PART II Getting Started; 6 Defining a Focused Problem; 7 Checking the Measurement System; 8 Choosing a Working Variation Reduction Approach; PART III Finding a Dominant Cause of Variation; 9 Finding a Dominant Cause Using the Method of Elimination; 10 Investigations to Compare Two Families of Variation.…”
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The ultimate algorithmic trading system toolbox + website : using today's technology to help you become a better trader by Pruitt, George, 1967-

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Reconstructive surgery of the hand and upper extremity by Germann, G. (Günter), 1952-, Levin, L. Scott, Sherman, R. (Randolph)

Table of Contents: “…Dorsal Soft Tissue Injury to Finger and Hand -- 24. Volar Soft Tissue Injury to Finger and Hand/Palm -- 25. …”
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Fundamentals of grid computing : theory, algorithms and technologies

Table of Contents: “…Cover; Title; Copyright; Contents; List of Figures; List of Tables; Foreword; Preface; Chapter 1: Grid computing overview; Chapter 2: Synchronization protocols for sharing resources in grid environments; Chapter 3: Data replication in grid environments; Chapter 4: Data management in grids; Chapter 5: Future of grids resources management; Chapter 6: Fault-tolerance and availability awareness in computational grids; Chapter 7: Fault tolerance for distributed scheduling in grids; Chapter 8: Broadcasting for grids; Chapter 9: Load balancing algorithms for dynamic networks.…”
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Specifics of decision making in modern business systems : regularities and tendencies

Table of Contents: “…5.2 Materials and Method5.3 Results; 5.4 Conclusions; References; 6. Algorithm of Making of Managerial Decisions in the Conditions of Constant Changes; 6.1 Introduction; 6.2 Materials and Method; 6.3 Results; 6.4 Theory as a Limitation during Making of Managerial Decisions; 6.5 Standards as a Limitation during Making of Managerial Decisions; 6.6 Time as a Limitation during Making of Managerial Decisions; 6.7 Risk as Limitation during Management of Managerial Decisions; 6.8 Forecasting as a Limitation during Making of Managerial Decisions…”
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Decision Intelligence for Dummies by Baker, Pamela

Table of Contents: “…Intro -- Title Page -- Copyright Page -- Table of Contents -- Introduction -- About This Book -- Conventions Used in This Book -- Foolish Assumptions -- What You Don't Have to Read -- How This Book Is Organized -- Part 1: Getting Started with Decision Intelligence -- Part 2: Reaching the Best Possible Decision -- Part 3: Establishing Reality Checks -- Part 4: Proposing a New Directive -- Part 5: The Part of Tens -- Icons Used in This Book -- Beyond the Book -- Where to Go from Here -- Part 1 Getting Started with Decision Intelligence -- Chapter 1 Short Takes on Decision Intelligence -- The Tale of Two Decision Trails -- Pointing out the way -- Making a decision -- Deputizing AI as Your Faithful Sidekick -- Seeing How Decision Intelligence Looks on Paper -- Tracking the Inverted V -- Estimating How Much Decision Intelligence Will Cost You -- Chapter 2 Mining Data versus Minding the Answer -- Knowledge Is Power - Data Is Just Information -- Experiencing the epiphany -- Embracing the new, not-so-new idea -- Avoiding thought boxes and data query borders -- Reinventing Actionable Outcomes -- Living with the fact that we have answers and still don't know what to do -- Going where humans fear to tread on data -- Ushering in The Great Revival: Institutional knowledge and human expertise -- Chapter 3 Cryptic Patterns and Wild Guesses -- Machines Make Human Mistakes, Too -- Seeing the Trouble Math Makes -- The limits of math-only approaches -- The right math for the wrong question -- Why data scientists and statisticians often make bad question-makers -- Identifying Patterns and Missing the Big Picture -- All the helicopters are broken -- MIA: Chunks of crucial but hard-to-get real-world data -- Evaluating man-versus-machine in decision-making -- Chapter 4 The Inverted V Approach -- Putting Data First Is the Wrong Move -- What's a decision, anyway?.…”
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Between stillness and motion : film, photography, algorithms

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