Tabla de Contenidos: “…9.5 Adding season or time of day to the streetcar delay prediction project -- 9.6 Imputation: An alternative to removing records with bad values -- 9.7 Making the web deployment of the streetcar delay prediction model generally available -- 9.8 Adapting the streetcar delay prediction model to a new dataset -- 9.9 Preparing the dataset and training the model -- 9.10 Deploying the model with web deployment -- 9.11 Deploying the model with Facebook Messenger -- 9.12 Adapting the approach in this book to a different dataset -- 9.13 Resources for additional learning -- Summary -- Appendix. …”

Tabla de Contenidos: “…Intro -- Title Page -- Copyright Page -- Table of Contents -- Introduction -- About This Book -- Foolish Assumptions -- Icons Used in This Book -- Beyond the Book -- Where to Go from Here -- Part 1 Techniques and Technologies -- Chapter 1 How Coding Benefits from AI -- Banishing Boring Tasks -- Spotting boring tasks -- Letting AI write the template -- Crafting CRUD with AI -- Helping with Syntax -- Stop remembering trivial details -- Hinting at code mastery -- Adapting to new syntax -- Linting with AI -- Detecting bad code with static code analysis -- Integrating AI with static code analysis -- Using AI as a Tutor -- Studying AI's potential in education -- Avoiding potential pitfalls -- Pairing Up with AI -- Overview of pair programming styles -- Understanding the pros and cons of pair programming with AI -- AI pair programming session -- Installing Copilot -- Using prompting to create a trivia game -- Chapter 2 Parsing Machine Learning and Deep Learning -- Decoding Machine and Deep Learning -- Defining key concepts -- Thinking about neural networks -- Input layer -- Hidden layer -- Output layer -- Training and testing models -- Demystifying Natural-Language Processing -- History of NLP -- Overcoming the challenges of NLP -- Understanding supervised and unsupervised learning -- Language generation techniques -- Understanding Transformers -- Learning to pay attention -- Getting tokens -- Illuminating Generative AI Models -- Recognizing AI's Limitations -- Language models are bad at math -- Language models are wordy -- AI has limited knowledge -- AI lacks common sense -- AI has accuracy issues -- AI has the potential to be biased -- Chapter 3 AI Coding Tools -- Navigating GitHub Copilot -- Installing the Copilot plug-in -- Working efficiently with Copilot -- Specify your goal -- Break things down -- Give examples -- Open related files…”

Tabla de Contenidos: “…Average word embeddings -- RNN-based document embeddings -- Transformer-based BERT embeddings -- SBERT embeddings -- Text clustering with Sentence-BERT -- Topic modeling with BERTopic -- Semantic search with SBERT -- Instruction fine-tuned embedding models -- Summary -- Further reading -- Chapter 8: Boosting Model Performance -- Technical requirements -- Improving performance with data augmentation -- Character-level augmentation -- Word-level augmentation -- Sentence-level augmentation -- Boosting IMDB text classification with augmentation -- Adapting the model to the domain -- Optimizing the parameters with HPO -- Summary -- Chapter 9: Parameter Efficient Fine-Tuning -- Technical requirements -- Introduction to PEFT -- Understanding Types of PEFT -- Additive methods -- Selective methods -- Low-rank fine-tuning -- Hands-on PEFT experiments -- Fine-tuning a BERT checkpoint with adapter tuning -- Efficiently fine-tune FLAN-T5 for an NLI task with Lora -- Tuning with QLoRA -- Summary -- References -- Part 3: Advanced Topics -- Chapter 10: Large Language Models -- Technical requirements -- Why large language models? …”

Tabla de Contenidos: “…Fraud detection model with differential privacy using the Opacus framework -- Differential privacy machine learning frameworks -- Limitations of differential privacy and strategies to overcome them -- Summary -- Part 3: Hands-On Federated Learning -- Chapter 6: Federated Learning and Implementing FL Using Open Source Frameworks -- Federated learning -- Preserving privacy -- FL definition -- Characteristics of FL -- FL algorithms -- FedSGD -- FedAvg -- Fed Adaptative Optimization -- The steps involved in implementing FL -- Open source frameworks to implement FL -- TensorFlow Federated -- Flower -- An end-to-end use case of implementing fraud detection using FL -- Developing an FL model for fraud detection using the Flower framework -- FL with differential privacy -- Approach one -- Approach two -- A sample application using FL-DP -- Summary -- Chapter 7: Federated Learning Benchmarks, Start-Ups, and the Next Opportunity -- FL benchmarks -- The importance of FL benchmarks -- FL datasets -- Frameworks for FL benchmarks -- Selecting an FL framework for a project -- A comparison of FedScale, FATE, Flower, and TensorFlow Federated -- State-of-the-art research in FL -- Communication-efficient FL -- Privacy-preserving FL -- Federated Meta-Learning -- Adaptive FL -- Federated reinforcement learning -- Key company products related to FL -- Summary -- Part 4: Homomorphic Encryption, SMC, Confidential Computing, and LLMs -- Chapter 8: Homomorphic Encryption and Secure Multiparty Computation -- Encryption, anonymization, and de-identification -- Data anonymization -- De-identification -- Exploring Homomorphic encryption -- Ring-based -- Lattice-based -- Elliptic curve-based -- Exploring the mathematics behind HE -- Encryption -- Homomorphism -- Types of HE -- Fully Homomorphic Encryption (FHE) -- Somewhat Homomorphic Encryption (SHE)…”

Tabla de Contenidos: “…Designing a longitudinal study on student relationships and perceived quality of life -- Chapter 20 Researching Links between Teacher Wellbeing and Educational Change: Case Studies from Kazakhstan and Sakha Republic -- chapter 21 Student contribution: Well-being at the Polish polar station, Svalbard: Adaptation to extreme environments -- Part IV Arcitc tourism. …”

Tabla de Contenidos: “…Yoon -- 5 NEPES’ Fan-Out Packaging Technology from Single die, SiP to Panel-Level Packaging 97 /Jong Heon (Jay) Kim -- 6 M-Series Fan-Out with Adaptive Patterning 117 /Tim Olson and Chris Scanlan -- 7 SWIFTR Semiconductor Packaging Technology 141 /Ron Huemoeller and Curtis Zwenger -- 8 Embedded Silicon Fan-Out (eSiFOR) Technology for Wafer-Level System Integration 169 /Daquan Yu -- 9 Embedding of Active and Passive Devices by Using an Embedded Interposer: The i2 Board Technology 185 /Thomas Gottwald, Christian Roessle, and Alexander Neumann -- 10 Embedding of Power Electronic Components: The Smart p2 Pack Technology 201 /Thomas Gottwald and Christian Roessle -- 11 Embedded Die in Substrate (Panel-Level) Packaging Technology 217 /Tomoko Takahashi and Akio Katsumata -- 12 Blade: A Chip-First Embedded Technology for Power Packaging 241 /Boris Plikat and Thorsten Scharf -- 13 The Role of Liquid Molding Compounds in the Success of Fan-Out Wafer-Level Packaging Technology 261 /Katsushi Kan, Michiyasu Sugahara, and Markus Cichon -- 14 Advanced Dielectric Materials (Polyimides and Polybenzoxazoles) for Fan-Out Wafer-Level Packaging (FO-WLP) 271 /T. …”

Tabla de Contenidos: “…Cover -- Copyright and Credits -- Packt Upsell -- Contributors -- Table of Contents -- Preface -- Chapter 1: Things to Know Before You Build a Drone -- Drone -- Types of drones -- How can we differentiate between drones -- Drone frames -- Types of motors used for drones -- Several types of speed controllers -- Flight control board -- Radio transmitter and receiver -- Battery -- Propellers -- Battery adapters/chargers -- Connectors -- Some modules to make the drone smarter -- Power distribution board -- Summary -- Chapter 2: Assembling Your Drone -- Assembling the frame -- Connecting the motors -- Connecting the ESC -- Connecting the ArduPilot -- Connecting the radio -- Connecting the RC receiver and transmitter -- Connecting the battery -- Binding transmitter to the receiver -- Know the aerodynamics needed for flying a drone -- Hovering -- Rising or climbing or taking off -- Dropping or descent or falling -- Yaw -- Pitch and roll -- Saving your drone from crashing -- Check things before flying -- Check the security protocols for flying a drone outside -- Summary -- Chapter 3: Preparing Your Drone for Flying -- What is ESP8266? …”

Tabla de Contenidos: “…7.5 Best-Candidate Sampling Patterns7.6 Adaptive Sampling; 7.7 Image Reconstruction; 7.8 Film and The Imaging Pipeline; Further Reading; Exercises; Chapter Eight: Reflection Models; 8.1 Basic Interface; 8.2 Specular Reflection and Transmission; 8.3 Lambertian Reflection; 8.4 Microfacet Models; 8.5 Fresnel Incidence Effects; 8.6 Measured BRDFs; Further Reading; Exercises; Chapter Nine: Materials; 9.1 BSDFs; 9.2 Material Interface and Implementations; 9.3 Bump Mapping; Further Reading; Exercises; Chapter Ten: Texture; 10.1 Sampling and Antialiasing; 10.2 Texture Coordinate Generation…”

Tabla de Contenidos: “…. -- Part II: The Agile Codex Theory -- Chapter 7: The Problem -- Plan for the Imperfect Plan -- Optimize for Adaptability -- Don't Surrender to Dependencies -- Chapter 8: The Codex -- The Principles of the Agile Codex -- Small Units of Work -- Sized -- Sequenceable -- Acyclic Dependency Tree -- Single Owner -- Application -- Chapter 9: The Agile -- Clear Ownership of Work at All Times in Each Stage -- Clear Inputs -- Clear Transition Criteria -- Clear Outputs -- Stakeholder Approval -- Chapter 10: Benefits -- Low Overhead -- Detailed Auditing -- Quick and Safe Deliveries -- Many Quality Gates -- Chapter 11: From Invention to Assembly Line -- The Importance of Dependencies -- Building the Assembly Line -- In Review -- Chapter 12: Team Functions -- User Experience (UX) -- Product Management (PM) -- Engineering Management (EM) -- Development (DEV) -- Quality Engineering (QE) -- Documentation (DOC) -- Operations (OPS) -- Customer Support Group (CSG) -- Chapter 13: Software Development Life Cycle -- Phases -- Planning -- Execution -- Releasing -- Choosing a Cadence -- How SDLC Length Affects Practices…”

Tabla de Contenidos: “…-- Moving average and autoregression -- Model selection and order -- Exponential smoothing -- ARCH and GARCH -- Vector autoregression -- Python libraries -- Statsmodels -- Python practice -- Requirements -- Modeling in Python -- Summary -- Chapter 6: Unsupervised Methods for Time-Series -- Unsupervised methods for time-series -- Anomaly detection -- Microsoft -- Google -- Amazon -- Facebook -- Twitter -- Implementations -- Change point detection -- Clustering -- Python practice -- Requirements -- Anomaly detection -- Change point detection -- Summary -- Chapter 7: Machine Learning Models for Time-Series -- More machine learning methods for time series -- Validation -- K-nearest neighbors with dynamic time warping -- Silverkite -- Gradient boosting -- Python exercise -- Virtual environments -- K-nearest neighbors with dynamic time warping in Python -- Silverkite -- Gradient boosting -- Ensembles with Kats -- Summary -- Chapter 8: Online Learning for Time-Series -- Online learning for time series -- Online algorithms -- Drift -- Drift detection methods -- Adaptive learning methods -- Python practice -- Drift detection -- Regression -- Model selection -- Summary -- Chapter 9: Probabilistic Models for Time-Series -- Probabilistic Models for Time-Series -- Prophet -- Markov Models -- Fuzzy Modeling -- Bayesian Structural Time-Series Models -- Python Exercise -- Prophet -- Markov Switching Model -- Fuzzy Time-Series -- Bayesian Structural Time-Series Modeling -- Summary -- Chapter 10: Deep Learning for Time-Series -- Introduction to deep learning -- Deep learning for time series -- Autoencoders -- InceptionTime -- DeepAR -- N-BEATS -- Recurrent neural networks -- ConvNets -- Transformer architectures -- Informer -- Python practice -- Fully connected network -- Recurrent neural network…”

Tabla de Contenidos: “…DBLINK_ENCRYPT_LOGINDB_NAME; DB_nK_CACHE_SIZE; DB_RECOVERY_FILE_DEST; DB_RECOVERY_FILE_DEST_SIZE; DB_RECYCLE_CACHE_SIZE; DB_UNIQUE_NAME; DDL_WAIT_FOR_LOCKS; DBWR_IO_SLAVES; DB_WRITER_PROCESSES; DISK_ASYNCH_IO; DISPATCHERS; DISTRIBUTED_TRANSACTIONS; DML_LOCKS; DRS_START; ENQUEUE_RESOURCES; ENT_DOMAIN_NAME; EVENT; FAL_CLIENT; FAL_SERVER; FAST_START_IO_TARGET; FAST_START_MTTR_TARGET; FAST_START_PARALLEL_ROLLBACK; FILEIO_NETWORK_ADAPTERS; FIXED_DATE; GC_DEFER_TIME; GC_FILES_TO_LOCKS; GC_LCK_PROCS; GC_RELEASABLE_LOCKS; GC_ROLLBACK_LOCKS; GCS_SERVER_PROCESSES; GLOBAL_NAMES; HASH_AREA_SIZE…”

Tabla de Contenidos: “…-- How have career guidance providers in Latin America adapted their offer in the context of the COVID-19 crisis? …”

Tabla de Contenidos: “…Becoming Agile Rapidly and Painlessly Individuals and Interactions Adapt or Die The Challenge 3. Transforming How We Work Innovating Is Learning Transforming Ideation From Insight to Disruption The World is Changed Transforming Execution: From Assumptions to Evidence Transforming Time: From Meetings to Productivity Transforming Organizations Summary: Eight Organizational Principles 4. …”

Tabla de Contenidos: “…The true RMA and the future of war? -- 7.2.3. Adaptation by networks? -- Conclusion -- Glossary -- Bibliography -- Index -- Other titles from iSTE in Information Systems, Web and Pervasive Computing -- EULA…”

Tabla de Contenidos: “…Cover -- Copyright -- Credits -- About the Authors -- About the Reviewer -- www.PacktPub.com -- Table of Contents -- Preface -- Chapter 1: Introducing Responsive Web Design -- Getting started with RWD -- Exploring how RWD works -- Understanding the elements of RWD -- Controlling the viewport -- Creating flexible grids -- Making media responsive -- Constructing suitable breakpoints -- Appreciating the importance of RWD -- Making our site accessible and intuitive -- Organizing our content -- Comparing RWD to adaptive design -- Preparing our development environment -- Considering a suitable strategy -- Exploring best practices -- Designing for touch -- Setting up a development workflow -- Discovering the requirements -- Planning our site -- Designing the text -- Sketching our design -- Prototyping and creating our design -- Testing our design -- Exploring mistakes -- Summary -- Chapter 2: Creating Fluid Layouts -- Introducing flexible grid layouts -- Understanding the different layout types -- Setting the available viewport for use -- Balancing viewport against experience -- Considering viewport units -- Exploring the benefits of flexible grid layouts -- Understanding the mechanics of grid layouts -- Implementing a prebuilt grid layout -- Exploring the use of flexbox -- Taking a closer look -- Visiting the future -- Implementing a basic gallery grid -- Exploring what happened -- Taking it further -- Summary -- Chapter 3: Adding Responsive Media -- Making media responsive -- Creating fluid images -- Implementing the &lt -- picture&gt -- element -- Using the srcset attribute -- Exploring the sizes attribute -- Manipulating the HTML5 &lt -- picture&gt -- element -- Putting it all together -- Exploring what happened -- Creating a real-world example -- Taking things further -- Making video responsive -- Embedding externally hosted videos…”

Tabla de Contenidos: “…1.3.2 Scale 1.3.3 Authority and Responsibility to Identify and Execute Risk-Response Measures; 1.3.4 Corporate Governance Guidelines; 1.3.5 General Organisational Effectiveness and the Creation of Competitive Advantage; 1.3.6 Quantification Requirements; 1.3.7 Reflecting Risk Tolerances in Decisions and in Business Design; 1.4 The Objectives and Uses of General Risk Assessment; 1.4.1 Adapt and Improve the Design and Structure of Plans and Projects; 1.4.2 Achieve Optimal Risk Mitigation within Revised Plans; 1.4.3 Evaluate Projects, Set Targets and Reflect Risk Tolerances in Decision-Making…”

Tabla de Contenidos: “…IntroductionGraphics AreasMajor ApplicationsGraphics APIsGraphics PipelineNumerical IssuesEfficiencyDesigning and Coding Graphics ProgramsMiscellaneous MathSets and MappingsSolving Quadratic EquationsTrigonometryVectorsCurves and SurfacesLinear InterpolationTrianglesRaster ImagesRaster DevicesImages, Pixels, and GeometryRGB ColorAlpha CompositingRay TracingThe Basic Ray-Tracing AlgorithmPerspectiveComputing Viewing RaysRay-Object IntersectionShadingA Ray-Tracing ProgramShadowsIdeal Specular ReflectionHistorical NotesLinear AlgebraDeterminantsMatricesComputing with Matrices and DeterminantsEigenvalues and Matrix DiagonalizationTransformation Matrices2D Linear Transformations3D Linear TransformationsTranslation and Affine TransformationsInverses of Transformation MatricesCoordinate TransformationsViewingViewing TransformationsProjective TransformationsPerspective ProjectionSome Properties of the Perspective TransformField-of-ViewThe Graphics PipelineRasterizationOperations Before and After RasterizationSimple AntialiasingCulling Primitives for EfficiencySignal ProcessingDigital Audio: Sampling in 1DConvolutionConvolution FiltersSignal Processing for ImagesSampling TheorySurface ShadingDiffuse ShadingPhong ShadingArtistic ShadingTexture MappingLooking Up Texture ValuesTexture Coordinate FunctionsAntialiasing Texture LookupsApplications of Texture MappingProcedural 3D TexturesData Structures for GraphicsTriangle MeshesScene GraphsSpatial Data StructuresBSP Trees for VisibilityTiling Multidimensional ArraysMore Ray TracingTransparency and RefractionInstancingConstructive Solid GeometryDistribution Ray TracingSamplingIntegrationContinuous ProbabilityMonte Carlo IntegrationChoosing Random PointsCurvesCurvesCurve PropertiesPolynomial PiecesPutting Pieces TogetherCubicsApproximating CurvesSummaryComputer AnimationPrinciples of AnimationKeyframingDeformationsCharacter AnimationPhysics-Based AnimationProcedural TechniquesGroups of ObjectsUsing Graphics HardwareHardware OverviewWhat Is Graphics HardwareHeterogeneous MultiprocessingGraphics Hardware Programming: Buffers, State, and ShadersState MachineBasic OpenGL Application LayoutGeometryA First Look at ShadersVertex Buffer ObjectsVertex Array ObjectsTransformation MatricesShading with Per-Vertex AttributesShading in the Fragment ProcessorMeshes and InstancingTexture ObjectsObject-Oriented Design for Graphics Hardware ProgrammingContinued LearningLightRadiometryTransport EquationPhotometryColorColorimetryColor SpacesChromatic AdaptationColor AppearanceVisual PerceptionVision ScienceVisual SensitivitySpatial VisionObjects, Locations, and EventsPicture PerceptionTone ReproductionClassificationDynamic RangeColorImage FormationFrequency-Based OperatorsGradient-Domain OperatorsSpatial OperatorsDivisionSigmoidsOther ApproachesNight TonemappingDiscussionImplicit ModelingImplicit Functions, Skeletal Primitives, and Summation BlendingRenderingSpace PartitioningMore on BlendingConstructive Solid GeometryWarpingPrecise Contact ModelingThe Blob TreeInteractive Implicit Modeling SystemsGlobal IlluminationParticle Tracing for Lambertian ScenesPath TracingAccurate Direct LightingReflection ModelsReal-World MaterialsImplementing Reflection ModelsSpecular Reflection ModelsSmooth-Layered ModelRough-Layered ModelComputer Graphics in GamesPlatformsLimited ResourcesOptimization TechniquesGame TypesThe Game Production ProcessVisualizationBackgroundData TypesHuman-Centered Design ProcessVisual Encoding PrinciplesInteraction PrinciplesComposite and Adjacent ViewsData ReductionExamples…”

Tabla de Contenidos: “…Chapter 2 Corporate and Sharī'ah Governance of Islamic Banks 2.1 Corporate Governance Gains Prominence; 2.2 Hisba System and an Islamic Perspective on Corporate Governance; 2.3 OECD and Islamic Principles of Corporate Governance; 2.4 Importance of Corporate Governance to Banking Sector; 2.5 The Financial Crisis and Corporate Governance Challenges; 2.6 Developing Countries and Corporate Governance Issues; 2.7 Corporate Governance Concerns for Islamic Banks; 2.8 IFSB and AAOIFI Issue Guidance; 2.9 Adapted Corporate Governance Understanding; 2.12 Sharīah Governance Model…”

Tabla de Contenidos: “…Frequency Representations""; ""3.2.7 Filter Banks""; ""3.2.8 Auto- and Cross-Correlation""; ""3.2.9 Cepstrum""; ""3.3 Digital Signal Processing (DSP)""; ""3.3.1 Sampling and Signal Conversion""; ""3.3.2 Z Transform""; ""3.3.3 Filters as LTI Systems""; ""3.3.4 Digital Filtering""; ""3.3.5 Linear Prediction""; ""3.3.6 Adaptive Filtering""; ""3.4 Hidden Markov Models""…”

Tabla de Contenidos: “…#031 Maximize Positive Interactions (MPI)#032 Follow Your Heart (FYH); #033 Check Before Promise (CBP); #034 Adapt Beginner's Mind (ABM); #035 Stop Doing Things (SDT); #036 Quantity Time Rules (QTR); #037 Rest Restore Recharge (RRR); #038 Change With Facts (CWF); #039 Never Give Up (NGU); #040 Be The Diplomat (BTD); #041 Build Positive Momentum (BPM); #042 Lead By Questions (LBQ); #043 Take It On (TIO); #044 Liked Or Respected (LOR); #045 Don't Do Lunch (DDL); #046 Face To Face (FTF); CHAPTER 5: Let Others Lead; #047 Awaken What's Within (AWW); #048 The Dolphin School (TDS)…”