Search Results - (((((((ant OR hands) OR planting) OR markant) 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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Hands-On Artificial Intelligence for IoT : Expert Machine Learning and Deep Learning Techniques for Developing Smarter IoT Systems. by Kapoor, Amita

Table of Contents: “…The convolution layerPooling layer; Some popular CNN model; LeNet to recognize handwritten digits; Recurrent neural networks; Long short-term memory; Gated recurrent unit; Autoencoders; Denoising autoencoders; Variational autoencoders; Summary; Chapter 5: Genetic Algorithms for IoT; Optimization; Deterministic and analytic methods; Gradient descent method; Newton-Raphson method; Natural optimization methods; Simulated annealing; Particle Swarm Optimization; Genetic algorithms; Introduction to genetic algorithms; The genetic algorithm; Crossover; Mutation; Pros and cons; Advantages…”
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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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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 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 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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Meta-heuristic and evolutionary algorithms for engineering optimization by Bozorg-Haddad, Omid, 1974-, Solgi, Mohammad, 1989-, Loaiciga, Hugo A.

Table of Contents: “…Overview of optimization -- Introduction to meta-heuristic and evolutionary algorithms -- Pattern search (PS) -- Genetic algorithm (GA) -- Simulated annealing (SA) -- Tabu search (TS) -- Ant colony optimization (ACO) -- Particle swarm optimization (PSO) -- Differential evolution (DE) -- Harmony search (HS) -- Shuffled frog-leaping algorithm (SFLA) -- Honey-bee mating optimization (HBMO) -- Invasive weed optimization (IWO) -- Central force optimization (CFO) -- Biogeography-based optimization (BBO) -- Firefly algorithm (FA) -- Gravity search algorithm (GSA) -- Bat algorithm (BA) -- Plant propagation algorithm (PPA) -- Water cycle algorithm (WCA) -- Symbiotic organisms search (SOS) -- Comprehensive evolutionary algorithm (CEA).…”
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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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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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Diffuse algorithms for neural and neuro-fuzzy networks : with applications in control engineering and signal processing by Skorohod, Boris A.

Table of Contents: “…Front Cover; Diffuse Algorithms for Neural and Neuro-Fuzzy Networks; Copyright Page; Contents; List of Figures; List of Tables; Preface; 1 Introduction; 1.1 Separable Models of Plants and Training Problems Associated With Them; 1.1.1 Separable Least Squares Method; 1.1.2 Perceptron With One Hidden Layer; 1.1.3 Radial Basis Neural Network; 1.1.4 Neuro-Fuzzy Network; 1.1.5 Plant Models With Time Delays; 1.1.6 Systems With Partly Unknown Dynamics; 1.1.7 Recurrent Neural Network; 1.1.8 Neurocontrol; 1.2 The Recursive Least Squares Algorithm With Diffuse and Soft Initializations.…”
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Algorithmic and artificial intelligence methods for protein bioinformatics

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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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Between stillness and motion : film, photography, algorithms

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Machine learning : hands-on for developers and technical professionals by Bell, Jason (Computer scientist)

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Deep learning with Python : a hands-on introduction by Ketkar, Nikhil

Table of Contents: “…Stochastic; Challenges with SGD; Local Minima; Saddle Points; Selecting the Learning Rate; Slow Progress in Narrow Valleys; Algorithmic Variations on SGD; Momentum.…”
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Hands-on Machine Learning with JavaScript : Solve complex computational web problems using machine learning. by Kanber, Burak

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Algorithmic problems of group theory, their complexity, and applications to cryptography

Table of Contents: “…Formal Definition -- 3. Shamirâ€?s Secret Sharing Scheme -- 4. Secret Sharing Using Non-commutative Groups -- 5. …”
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