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Official Google Cloud Certified Professional Data Engineer study guide by Sullivan, Dan, 1962-

Table of Contents: “…Row Key Access 13 -- Unstructured Data 15 -- Google's Storage Decision Tree 16 -- Schema Design Considerations 16 -- Relational Database Design 17 -- NoSQL Database Design 20 -- Exam Essentials 23 -- Review Questions 24 -- Chapter 2 Building and Operationalizing Storage Systems 29 -- Cloud SQL 30 -- Configuring Cloud SQL 31 -- Improving Read Performance with Read Replicas 33 -- Importing and Exporting Data 33 -- Cloud Spanner 34 -- Configuring Cloud Spanner 34 -- Replication in Cloud Spanner 35 -- Database Design Considerations 36 -- Importing and Exporting Data 36 -- Cloud Bigtable 37 -- Configuring Bigtable 37 -- Database Design Considerations 38 -- Importing and Exporting 39 -- Cloud Firestore 39 -- Cloud Firestore Data Model 40 -- Indexing and Querying 41 -- Importing and Exporting 42 -- BigQuery 42 -- BigQuery Datasets 43 -- Loading and Exporting Data 44 -- Clustering, Partitioning, and Sharding Tables 45 -- Streaming Inserts 46 -- Monitoring and Logging in BigQuery 46 -- BigQuery Cost Considerations 47 -- Tips for Optimizing BigQuery 47 -- Cloud Memorystore 48 -- Cloud Storage 50 -- Organizing Objects in a Namespace 50 -- Storage Tiers 51 -- Cloud Storage Use Cases 52 -- Data Retention and Lifecycle Management 52 -- Unmanaged Databases 53 -- Exam Essentials 54 -- Review Questions 56 -- Chapter 3 Designing Data Pipelines 61 -- Overview of Data Pipelines 62 -- Data Pipeline Stages 63 -- Types of Data Pipelines 66 -- GCP Pipeline Components 73 -- Cloud Pub/Sub 74 -- Cloud Dataflow 76 -- Cloud Dataproc 79 -- Cloud Composer 82 -- Migrating Hadoop and Spark to GCP 82 -- Exam Essentials 83 -- Review Questions 86 -- Chapter 4 Designing a Data Processing Solution 89 -- Designing Infrastructure 90 -- Choosing Infrastructure 90 -- Availability, Reliability, and Scalability of Infrastructure 93 -- Hybrid Cloud and Edge Computing 96 -- Designing for Distributed Processing 98 -- Distributed Processing: Messaging 98 -- Distributed Processing: Services 101 -- Migrating a Data Warehouse 102 -- Assessing the Current State of a Data Warehouse 102 -- Designing the Future State of a Data Warehouse 103 -- Migrating Data, Jobs, and Access Controls 104 -- Validating the Data Warehouse 105 -- Exam Essentials 105 -- Review Questions 107 -- Chapter 5 Building and Operationalizing Processing Infrastructure 111 -- Provisioning and Adjusting Processing Resources 112 -- Provisioning and Adjusting Compute Engine 113 -- Provisioning and Adjusting Kubernetes Engine 118 -- Provisioning and Adjusting Cloud Bigtable 124 -- Provisioning and Adjusting Cloud Dataproc 127 -- Configuring Managed Serverless Processing Services 129 -- Monitoring Processing Resources 130 -- Stackdriver Monitoring 130 -- Stackdriver Logging 130 -- Stackdriver Trace 131 -- Exam Essentials 132 -- Review Questions 134 -- Chapter 6 Designing for Security and Compliance 139 -- Identity and Access Management with Cloud IAM 140 -- Predefined Roles 141 -- Custom Roles 143 -- Using Roles with Service Accounts 145 -- Access Control with Policies 146 -- Using IAM with Storage and Processing Services 148 -- Cloud Storage and IAM 148 -- Cloud Bigtable and IAM 149 -- BigQuery and IAM 149 -- Cloud Dataflow and IAM 150 -- Data Security 151 -- Encryption 151 -- Key Management 153 -- Ensuring Privacy with the Data Loss Prevention API 154 -- Detecting Sensitive Data 154 -- Running Data Loss Prevention Jobs 155 -- Inspection Best Practices 156 -- Legal Compliance 156 -- Health Insurance Portability and Accountability Act (HIPAA) 156 -- Children's Online Privacy Protection Act 157 -- FedRAMP 158 -- General Data Protection Regulation 158 -- Exam Essentials 158 -- Review Questions 161 -- Chapter 7 Designing Databases for Reliability, Scalability, and Availability 165 -- Designing Cloud Bigtable Databases for Scalability and Reliability 166 -- Data Modeling with Cloud Bigtable 166 -- Designing Row-keys 168 -- Designing for Time Series 170 -- Use Replication for Availability and Scalability 171 -- Designing Cloud Spanner Databases for Scalability and Reliability 172 -- Relational Database Features 173 -- Interleaved Tables 174 -- Primary Keys and Hotspots 174 -- Database Splits 175 -- Secondary Indexes 176 -- Query Best Practices 177 -- Designing BigQuery Databases for Data Warehousing 179 -- Schema Design for Data Warehousing 179 -- Clustered and Partitioned Tables 181 -- Querying Data in BigQuery 182 -- External Data Access 183 -- BigQuery ML 185 -- Exam Essentials 185 -- Review Questions 188 -- Chapter 8 Understanding Data Operations for Flexibility and Portability 191 -- Cataloging and Discovery with Data Catalog 192 -- Searching in Data Catalog 193 -- Tagging in Data Catalog 194 -- Data Preprocessing with Dataprep 195 -- Cleansing Data 196 -- Discovering Data 196 -- Enriching Data 197 -- Importing and Exporting Data 197 -- Structuring and Validating Data 198 -- Visualizing with Data Studio 198 -- Connecting to Data Sources 198 -- Visualizing Data 200 -- Sharing Data 200 -- Exploring Data with Cloud Datalab 200 -- Jupyter Notebooks 201 -- Managing Cloud Datalab Instances 201 -- Adding Libraries to Cloud Datalab Instances 202 -- Orchestrating Workflows with Cloud Composer 202 -- Airflow Environments 203 -- Creating DAGs 203 -- Airflow Logs 204 -- Exam Essentials 204 -- Review Questions 206 -- Chapter 9 Deploying Machine Learning Pipelines 209 -- Structure of ML Pipelines 210 -- Data Ingestion 211 -- Data Preparation 212 -- Data Segregation 215 -- Model Training 217 -- Model Evaluation 218 -- Model Deployment 220 -- Model Monitoring 221 -- GCP Options for Deploying Machine Learning Pipeline 221 -- Cloud AutoML 221 -- BigQuery ML 223 -- Kubeflow 223 -- Spark Machine Learning 224 -- Exam Essentials 225 -- Review Questions 227 -- Chapter 10 Choosing Training and Serving Infrastructure 231 -- Hardware Accelerators 232 -- Graphics Processing Units 232 -- Tensor Processing Units 233 -- Choosing Between CPUs, GPUs, and TPUs 233 -- Distributed and Single Machine Infrastructure 234 -- Single Machine Model Training 234 -- Distributed Model Training 235 -- Serving Models 236 -- Edge Computing with GCP 237 -- Edge Computing Overview 237 -- Edge Computing Components and Processes 239 -- Edge TPU 240 -- Cloud IoT 240 -- Exam Essentials 241 -- Review Questions 244 -- Chapter 11 Measuring, Monitoring, and Troubleshooting Machine Learning Models 247 -- Three Types of Machine Learning Algorithms 248 -- Supervised Learning 248 -- Unsupervised Learning 253 -- Anomaly Detection 254 -- Reinforcement Learning 254 -- Deep Learning 255 -- Engineering Machine Learning Models 257 -- Model Training and Evaluation 257 -- Operationalizing ML Models 262 -- Common Sources of Error in Machine Learning Models 263 -- Data Quality 264 -- Unbalanced Training Sets 264 -- Types of Bias 264 -- Exam Essentials 265 -- Review Questions 267 -- Chapter 12 Leveraging Prebuilt Models as a Service 269 -- Sight 270 -- Vision AI 270 -- Video AI 272 -- Conversation 274 -- Dialogflow 274 -- Cloud Text-to-Speech API 275 -- Cloud Speech-to-Text API 275 -- Language 276 -- Translation 276 -- Natural Language 277 -- Structured Data 278 -- Recommendations AI API 278 -- Cloud Inference API 280 -- Exam Essentials 280 -- Review Questions 282 -- Appendix Answers to Review Questions 285 -- Chapter 1: Selecting Appropriate Storage Technologies 286 -- Chapter 2: Building and Operationalizing Storage Systems 288 -- Chapter 3: Designing Data Pipelines 290 -- Chapter 4: Designing a Data Processing Solution 291 -- Chapter 5: Building and Operationalizing Processing Infrastructure 293 -- Chapter 6: Designing for Security and Compliance 295 -- Chapter 7: Designing Databases for Reliability, Scalability, and Availability 296 -- Chapter 8: Understanding Data Operations for Flexibility and Portability 298 -- Chapter 9: Deploying Machine Learning Pipelines 299 -- Chapter 10: Choosing Training and Serving Infrastructure 301 -- Chapter 11: Measuring, Monitoring, and Troubleshooting Machine Learning Models 303 -- Chapter 12: Leveraging Prebuilt Models as a Service 304 -- Index 307.…”
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Towards human-UAV physical interaction and fully actuated aerial vehicles by Rajappa, Sujit

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Goliath's revenge : how established companies turn the tables on digital disruptors by Hewlin, Todd, Snyder, Scott A. (Scott Andrew), 1965-

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PID and predictive control of electrical drives and power supplies using MATLAB/Simulink by Wang, Liuping

Table of Contents: “…5.7 Tuning PI Control Systems for Power Converter 147 -- 5.7.1 Overview of the Designs 147 -- 5.7.2 Tuning the Current Controllers 149 -- 5.7.3 Tuning Voltage Controller 150 -- 5.7.4 Experimental Evaluations 154 -- 5.8 Tuning P Plus PI Controllers for Power Converter 157 -- 5.8.1 Design and Sensitivity Functions 157 -- 5.8.2 Experimental Results 158 -- 5.9 Robustness of Power Converter Control System Using PI Current Controllers 159 -- 5.9.1 Variation of Inductance Using PI Current Controllers 160 -- 5.9.2 Variation of Capacitance on Closed-loop Performance 163 -- 5.10 Summary 167 -- 5.10.1 Current Controllers 167 -- 5.10.2 Velocity, Position and Voltage Controllers 168 -- 5.10.3 Choice between P Current Control and PI Current Control 169 -- 5.11 Further Reading 169 -- References 169 -- 6 FCS Predictive Control in d − q Reference Frame 171 -- 6.1 States of IGBT Inverter and the Operational Constraints 172 -- 6.2 FCS Predictive Control of PMSM 175 -- 6.3 MATLAB Tutorial on Real-time Implementation of FCS-MPC 177 -- 6.3.1 Simulation Results 179 -- 6.3.2 Experimental Results of FCS Control 181 -- 6.4 Analysis of FCS-MPC System 182 -- 6.4.1 Optimal Control System 182 -- 6.4.2 Feedback Controller Gain 184 -- 6.4.3 Constrained Optimal Control 185 -- 6.5 Overview of FCS-MPC with Integral Action 187 -- 6.6 Derivation of I-FCS Predictive Control Algorithm 191 -- 6.6.1 Optimal Control without Constraints 191 -- 6.6.2 I-FCS Predictive Controller with Constraints 194 -- 6.6.3 Implementation of I-FCS-MPC Algorithm 196 -- 6.7 MATLAB Tutorial on Implementation of I-FCS Predictive Controller 197 -- 6.7.1 Simulation Results 198 -- 6.8 I-FCS Predictive Control of Induction Motor 201 -- 6.8.1 The Control Algorithm for an Induction Motor 202 -- 6.8.2 Simulation Results 204 -- 6.8.3 Experimental Results 205 -- 6.9 I-FCS Predictive Control of Power Converter 209 -- 6.9.1 I-FCS Predictive Control of a Power Converter 209 -- 6.9.2 Simulation Results 211 -- 6.9.3 Experimental Results 214.…”
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XML for DB2 information integration

Table of Contents: “…-- 3.4 Creating an XML schema from a database schema -- 3.4.1 The algorithm.…”
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IBM TotalStorage : SAN product, design, and optimization guide

Table of Contents: “…-- 1.1.2 The Internet brings increased risks -- 1.1.3 Planning for business continuity -- 1.2 Using a SAN for business continuance -- 1.2.1 SANs and business continuance -- 1.3 SAN business benefits -- 1.3.1 Storage consolidation and sharing of resources -- 1.3.2 Data sharing -- 1.3.3 Nondisruptive scalability for growth -- 1.3.4 Improved backup and recovery -- 1.3.5 High performance -- 1.3.6 High availability server clustering -- 1.3.7 Improved disaster tolerance -- 1.3.8 Allow selection of best of breed storage -- 1.3.9 Ease of data migration -- 1.3.10 Reduced total costs of ownership -- 1.3.11 Storage resources match e-business enterprise needs -- Chapter 2. …”
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Penetration testing : a hands-on introduction to hacking by Weidman, Georgia

Table of Contents: “…Metasploit Payloads / Peter Van Eeckhoutte -- Meterpreter / Peter Van Eeckhoutte -- Exploiting WebDAV Default Credentials / Peter Van Eeckhoutte -- Running a Script on the Target Web Server / Peter Van Eeckhoutte -- Uploading a Msfvenom Payload / Peter Van Eeckhoutte -- Exploiting Open phpMyAdmin / Peter Van Eeckhoutte -- Downloading a File with TFTP / Peter Van Eeckhoutte -- Downloading Sensitive Files / Peter Van Eeckhoutte -- Downloading a Configuration File / Peter Van Eeckhoutte -- Downloading the Windows SAM / Peter Van Eeckhoutte -- Exploiting a Buffer Overflow in Third-Party Software / Peter Van Eeckhoutte -- Exploiting Third-Party Web Applications / Peter Van Eeckhoutte -- Exploiting a Compromised Service / Peter Van Eeckhoutte -- Exploiting Open NFS Shares / Peter Van Eeckhoutte -- Summary / Peter Van Eeckhoutte -- 9. …”
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Software engineering for embedded systems : methods, practical techniques, and applications

Table of Contents: “…-- Kinds of software reuse -- Implementing reuse by layers -- Going to the next level -- Introducing the component factory -- Factory hardware configuration -- Factory software configuration -- How the factory aids reusability -- RTOS agnosticism -- Arbitrary extensibility -- Conclusion -- References -- Example: latency vs. throughput in an eNodeB application -- Performance patterns and anti-patterns -- References -- The code optimization process -- Using the development tools -- Compiler optimization -- Basic compiler configuration -- Enabling optimizations -- Additional optimization configurations -- Using the profiler -- Background -- understanding the embedded architecture -- Resources -- Basic C optimization techniques -- Choosing the right data types -- Functions calling conventions -- Pointers and memory access -- Restrict and pointer aliasing -- Loops -- Additional tips and tricks -- General loop transformations -- Loop unrolling -- Multisampling -- Partial summation -- Software pipelining -- Example application of optimization techniques: cross-correlation -- Setup -- Original implementation -- Step 1: use intrinsics for fractional operations and specify loop counts -- Step 2: specify data alignment and modify for multisampling algorithm -- Step 3: assembly-language optimization -- Introduction -- Code size optimizations -- Compiler flags and flag mining -- Target ISA for size and performance tradeoffs -- Tuning the ABI for code size -- Caveat emptor: compiler optimization orthogonal to code size! …”
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Ocular therapeutics handbook : a clinical manual

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Sigma-Delta Converters. by De la Rosa, José M.

Table of Contents: “…6.3.1 Hardware Emulation of CT-Ms on an FPGA 257 -- 6.3.2 GPU-accelerated Computing of CT-Ms 258 -- 6.4 Using Multi-objective Evolutionary Algorithms to Optimize Ms 259 -- 6.4.1 Combining MOEA with SIMSIDES 261 -- 6.4.2 Applying MOEA and SIMSIDES to the Synthesis of CT-Ms 262 -- 6.5 Summary 269 -- References 269 -- 7 Electrical Design of ??…”
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Public safety networks from LTE to 5G by Yarali, Abdulrahman

Table of Contents: “…9.2.5 Flexibility 164 -- 9.3 Starting Public Safety Implementation Versus Waiting for 5G 165 -- 9.4 5GVersus 4G Public Safety Services 166 -- 9.4.1 Video Surveillance 167 -- 9.4.2 Computer-Driven Augmented Reality (AR) Helmet 167 -- 9.5 How 5GWill Shape Emergency Services 167 -- 9.6 4G LTE Defined Public Safety Content in 5G 168 -- 9.7 The Linkage Between 4G-5G Evolution and the Spectrum for Public Safety 168 -- 9.8 Conclusion 168 -- References 168 -- 10 Fifth Generation (5G) Cellular Technology 171 -- 10.1 Introduction 171 -- 10.2 Background Information on Cellular Network Generations 172 -- 10.2.1 Evolution of Mobile Technologies 172 -- 10.2.1.1 First Generation (1G) 172 -- 10.2.1.2 Second Generation (2G) Mobile Network 172 -- 10.2.1.3 Third Generation (3G) Mobile Network 172 -- 10.2.1.4 Fourth Generation (4G) Mobile Network 173 -- 10.2.1.5 Fifth Generation (5G) 173 -- 10.3 Fifth Generation (5G) and the Network of Tomorrow 174 -- 10.3.1 5G Network Architecture 176 -- 10.3.2 Wireless Communication Technologies for 5G 177 -- 10.3.2.1 Massive MIMO 177 -- 10.3.2.2 Spatial Modulation 179 -- 10.3.2.3 Machine to Machine Communication (M2M) 179 -- 10.3.2.4 Visible Light Communication (VLC) 180 -- 10.3.2.5 Green Communications 180 -- 10.3.3 5G System Environment 180 -- 10.3.4 Devices Used in 5G Technology 181 -- 10.3.5 Market Standardization and Adoption of 5G Technology 181 -- 10.3.6 Security Standardization of Cloud Applications 183 -- 10.3.7 The Global ICT Standardization Forum for India (GISFI) 184 -- 10.3.8 Energy Efficiency Enhancements 184 -- 10.3.9 Virtualization in the 5G Cellular Network 185 -- 10.3.10 Key Issues in the Development Process 185 -- 10.3.10.1 Challenges of Heterogeneous Networks 186 -- 10.3.10.2 Challenges Caused by Massive MIMO Technology 186 -- 10.3.10.3 Big Data Problem 186 -- 10.3.10.4 Shared Spectrum 186 -- 10.4 Conclusion 187 -- References 187 -- 11 Issues and Challenges of 4G and 5G for PS 189 -- 11.1 Introduction 189 -- 11.2 4G and 5GWireless Connections 190.…”
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Visual Inspection Technology in the Hard Disc Drive Industry. by Muneesawang, Paisarn

Table of Contents: “…Introduction / Suchart Yammen / Paisarn Muneesawang -- 1.2. Algorithm for corrosion detection / Suchart Yammen / Paisarn Muneesawang -- 1.2.1. …”
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Fundamentals of Fluid Power Control. by Watton, John

Table of Contents: “…Control-Volume Flow Continuity -- PRV Flow -- Force Balance at the Spindle -- 5.13.3 Frequency Response from a Linearized Transfer Function Analysis -- 5.14 Servovalve Dynamics -- First-Stage, Armature, and Flapper-Nozzle -- Flapper-Nozzle and Resistance Bridge Flow Characteristic -- Force Balance at the Spool -- 5.15 An Open-Loop Servovalve-Motor Drive with Line Dynamics Modeled by Lumped Approximations -- Servovalve, Dynamics Included, Underlapped Spool -- Lines, Laminar Mean Flow, Two Lump Approximations per Line, Negligible Motor Internal Volume -- Motor Flow and Torque Equations -- 5.16 Transmission Line Dynamics -- 5.16.1 Introduction -- Servovalve-Cylinder with Short Lines and Significant Actuator Volumes -- Servovalve-Motor with Long Lines and Negligible Actuator Volumes -- 5.16.2 Lossless Line Model for Z and Y -- 5.16.3 Average and Distributed Line Friction Models for Z and Y -- 5.16.4 Frequency-Domain Analysis -- 5.16.5 Servovalve-Reflected Linearized Coefficients -- 5.16.6 Modeling Systems with Nonlossless Transmission Lines, the Modal Analysis Method -- 5.16.7 Modal Analysis Applied to a Servovalve-Motor Open-Loop Drive -- 5.17 The State-Space Method for Linear Systems Modeling -- 5.17.1 Modeling Principles -- 5.17.2 Some Further Aspects of the Time-Domain Solution -- 5.17.3 The Transfer Function Concept in State Space -- 5.18 Data-Based Dynamic Modeling -- 5.18.1 Introduction -- 5.18.2 Time-Series Modeling -- 5.18.3 The Group Method of Data Handling (GMDH) Algorithm -- 5.18.4 Artificial Neural Networks -- 5.18.5 A Comparison of Time-Series, GMDH, and ANN Modeling of a Second-Order Dynamic System -- 5.18.6 Time-Series Modeling of a Position Control System -- 5.18.7 Time-Series Modeling for Fault Diagnosis -- 5.18.8 Time-Series Modeling of a Proportional PRV -- 5.18.9 GMDH Modeling of a Nitrogen-Filled Accumulator.…”
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Systemic architecture : operating manual for the self-organizing city by Poletto, Marco

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Dynamics among nations : the evolution of legitimacy and development in modern states by Root, Hilton L.

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Teaching primary programming with Scratch : research-informed approaches. Teacher book by Bagge, Phil

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Power system monitoring and control by Bevrani, Hassan

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Big Data Analytics with R. by Walkowiak, Simon

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