“…Algorithms and Networking for Computer Games is an essential guide to solving the algorithmic and networking problems of modern commercial computer games, written from the perspective of a computer scientist. Combining algorithmic knowledge and game-related problems, the authors discuss all the common difficulties encountered in game programming. …”

“…Leverage the power of Matplotlib to visualize and understand your data more effectively About This Book Perform effective data visualization with Matplotlib and get actionable insights from your data Design attractive graphs, charts, and 2D plots, and deploy them to the web Get the most out of Matplotlib in this practical guide with updated code and examples Who This Book Is For This book is essentially for anyone who wants to create intuitive data visualizations using the Matplotlib library. If you're a data scientist or analyst and wish to create attractive visualizations using Python, you'll find this book useful. …”

“…Build next-generation Artificial Intelligence systems with Java About This Book Implement AI techniques to build smart applications using Deeplearning4j Perform big data analytics to derive quality insights using Spark MLlib Create self-learning systems using neural networks, NLP, and reinforcement learning Who This Book Is For This book is for you if you are a data scientist, big data professional, or novice who has basic knowledge of big data and wish to get proficiency in Artificial Intelligence techniques for big data. …”

Tabla de Contenidos: “…Spark pipelines for dataset preprocessing -- Dataset preprocessing automation -- Summary -- Chapter 3: A Holistic View on Spark -- Spark for a holistic view -- The use case -- Fast and easy computing -- Methods for a holistic view -- Regression modeling -- The SEM approach -- Decision trees -- Feature preparation -- PCA -- Grouping by category to use subject knowledge -- Feature selection -- Model estimation -- MLlib implementation -- The R notebooks' implementation -- Model evaluation -- Quick evaluations -- RMSE -- ROC curves -- Results explanation -- Impact assessments -- Deployment -- Dashboard -- Rules -- Summary -- Chapter 4: Fraud Detection on Spark -- Spark for fraud detection -- The use case -- Distributed computing -- Methods for fraud detection -- Random forest -- Decision trees -- Feature preparation -- Feature extraction from LogFile -- Data merging -- Model estimation -- MLlib implementation -- R notebooks implementation -- Model evaluation -- A quick evaluation -- Confusion matrix and false positive ratios -- Results explanation -- Big influencers and their impacts -- Deploying fraud detection -- Rules -- Scoring -- Summary -- Chapter 5: Risk Scoring on Spark -- Spark for risk scoring -- The use case -- Apache Spark notebooks -- Methods of risk scoring -- Logistic regression -- Preparing coding in R -- Random forest and decision trees -- Preparing coding -- Data and feature preparation -- OpenRefine -- Model estimation -- The DataScientistWorkbench for R notebooks -- R notebooks implementation -- Model evaluation -- Confusion matrix -- ROC -- Kolmogorov-Smirnov -- Results explanation -- Big influencers and their impacts -- Deployment -- Scoring -- Summary -- Chapter 6: Churn Prediction on Spark -- Spark for churn prediction -- The use case -- Spark computing -- Methods for churn prediction -- Regression models…”

Tabla de Contenidos: “…Cover -- Copyright -- Credits -- About the Author -- About the Reviewers -- www.PacktPub.com -- Table of Contents -- Preface -- Chapter 1: How to Sound Like a Data Scientist -- What is data science? -- Basic terminology -- Why data science? …”

Tabla de Contenidos: “…Intro -- Title Page -- Copyright Page -- Contents -- Preface -- Acknowledgements -- Part I Basics -- Chapter 1 Introduction to Nanotechnology -- 1.1 Nanotechnology: From Large to Small -- 1.1.1 Feynman: Plenty of Room at the Bottom -- 1.1.2 Nanotechnology Today -- 1.1.3 The Bottom‐Up Approach -- 1.2 Nanocarbons: Now and Then -- 1.2.1 Classification -- 1.2.2 Fullerenes -- 1.2.3 Carbon Nanotubes -- 1.2.4 Graphenes -- References -- Chapter 2 Nanodiamonds -- 2.1 Ah, Diamonds, Eternal Beautiful -- 2.2 Diamonds: From Structure to Classification -- 2.2.1 Structure -- 2.3 Diamond Synthesis -- 2.3.1 HPHT -- 2.3.2 CVD -- 2.3.3 Detonation -- 2.4 Nanodiamonds: A Scientist's Best Friend -- References -- Chapter 3 Color Centers in Diamond -- 3.1 Nitrogen Impurities -- 3.2 Crystal Defects -- 3.3 Vacancy‐Related Color Centers -- 3.3.1 GR1 and ND1 -- 3.3.2 NV0 and NV− -- 3.3.3 H3 and N3 -- 3.3.4 SiV− -- 3.4 The NV− Center -- References -- Chapter 4 Surface Chemistry of Nanodiamonds -- 4.1 Functionalization -- 4.2 Bioconjugation -- 4.2.1 Noncovalent Conjugation -- 4.2.2 Covalent Conjugation -- 4.3 Encapsulation -- 4.3.1 Lipid Layers -- 4.3.2 Silica Shells -- References -- Chapter 5 Biocompatibility of Nanodiamonds -- 5.1 Biocompatibility Testing -- 5.1.1 Cytotoxicity -- 5.1.2 Genotoxicity -- 5.1.3 Hemocompatibility -- 5.2 In Vitro Studies -- 5.2.1 HPHT‐ND -- 5.2.2 DND -- 5.3 Ex Vivo Studies -- 5.4 In Vivo Studies -- References -- Part II Specific Topics -- Chapter 6 Producing Fluorescent Nanodiamonds -- 6.1 Production -- 6.1.1 Theoretical Simulations -- 6.1.2 Electron/Ion Irradiation -- 6.1.3 Size Reduction -- 6.2 Characterization -- 6.2.1 Fluorescence Intensity -- 6.2.2 Electron Spin Resonance -- 6.2.3 Fluorescence Lifetime -- 6.2.4 Magnetically Modulated Fluorescence -- References -- Chapter 7 Single Particle Detection and Tracking…”

Tabla de Contenidos: “…Public Engagement with Science During and about COVID-19 via Twitter: Who, When, What, and How -- Introduction -- Related work -- Health communication on social media -- Public engagement with science via social media -- The level of engagement on social media -- Methodology -- Data collection -- Data analysis -- Findings -- RQ1: What and how are tweets posted during and about COVID-19 by scientists, pseudo-experts, and public health organizations? …”

Tabla de Contenidos: “…Choosing at the Margin -- Choices Respond to Incentives -- Economics as Social Science and Policy Tool -- Economist as Social Scientist -- Economist as Policy Adviser -- Economists in the Economy -- Jobs for an Economics Major -- Will Jobs for Economics Majors Grow? …”

Tabla de Contenidos: “…Choosing at the Margin -- Choices Respond to Incentives -- Economics As Social Science And Policy Tool -- Economist as Social Scientist -- Economist as Policy Adviser -- Economists in the Economy -- Jobs for an Economics Major -- Will Jobs for Economics Majors Grow? …”

Tabla de Contenidos: “…-- Analytics on AWS -- Skills Required to Build and Maintain an AWS Analytics Pipeline -- Chapter 2 The Path to Analytics: Setting Up a Data and Analytics Team -- The Data Vision -- Support -- DA Team Roles -- Early Stage Roles -- Team Lead -- Data Architect -- Data Engineer -- Data Analyst -- Maturity Stage Roles -- Data Scientist -- Cloud Engineer -- Business Intelligence (BI) Developer -- Machine Learning Engineer -- Business Analyst -- Niche Roles -- Analytics Flow at a Process Level -- Workflow Methodology -- The DA Team Mantra: "Automate Everything" -- Analytics Models in the Wild: Centralized, Distributed, Center of Excellence -- Centralized -- Distributed -- Center of Excellence -- Summary -- Chapter 3 Working on AWS -- Accessing AWS -- Everything Is a Resource -- S3: An Important Exception -- IAM: Policies, Roles, and Users -- Policies -- Identity-Based Policies -- Resource-Based Policies -- Roles -- Users and User Groups -- Summarizing IAM -- Working with the Web Console -- The AWS Command-Line Interface -- Installing AWS CLI -- Linux Installation -- macOS Installation -- Windows -- Configuring AWS CLI -- A Note on Region -- Setting Individual Parameters -- Using Profiles and Configuration Files -- Final Notes on Configuration -- Using the AWS CLI -- Using Skeletons and File Inputs -- Cleaning Up!…”

“…About This Book Understand how Spark can be distributed across computing clusters Develop and run Spark jobs efficiently using Python A hands-on tutorial by Frank Kane with over 15 real-world examples teaching you Big Data processing with Spark Who This Book Is For If you are a data scientist or data analyst who wants to learn Big Data processing using Apache Spark and Python, this book is for you. …”

Tabla de Contenidos: “…-- the EV3 software -- the structure of this book -- the companion website -- let's start already! -- comic: the EV3L scientist's apprentice -- 1. your LEGO MINDSTORMS EV3 set -- the studless way of building -- studless vs. studded: the structural differences -- naming the pieces -- beams -- straight beams -- angular beams -- frames -- thin beams and links -- connectors -- pins and axle pins -- axles and bushes -- axle, pin, and angle connectors -- cross blocks -- gears -- wheels, tires, and treads -- decorative pieces -- miscellaneous pieces -- electronic pieces -- the differences between the EV3 retail and education sets -- conclusion -- Comic: continued -- 2. building ROV3R -- base module -- ROV3R with wheels -- touch sensor bumper -- ROV3R with touch sensor bumper -- line-following module -- line-following ROV3R -- front IR sensor -- ROV3R with front IR sensor -- wall-following module -- wall-following ROV3R -- alternative: ROV3R with wall-following and line-following modules -- Dexter's cleaning tool -- ROV3R with cleaning tool -- alternative #1: ROV3R with cleaning tool and touch sensor bumper -- alternative #2: wall-following ROV3R with cleaning tool -- ROV3R with treads -- secret project: grabber module -- conclusion -- Comic continued -- 3. programming -- the building blocks of any program -- sequences -- choices -- loops -- programming with the brick program app -- your first brick program -- the block palette -- the action blocks -- the move block -- the large motor block -- the medium motor block…”

Tabla de Contenidos: “…Architectural Considerations for the Data Scientist -- Data Discovery and Acquisition -- Exploratory Data Analysis -- Data Preparation -- Feature Engineering -- Model Build and Selection -- Model Evaluation and Testing -- Model Deployment -- Model Monitoring -- Legality and Ethical Use of Data -- Automation and ML -- The Real World is Different than University -- Do You Know How to Bake Bread? …”

“…Whether you're a data scientist, analyst, machine learning engineer, or Python developer, this book will empower you to design modular systems for data preparation, accurately train and test models, and seamlessly integrate them into larger technologies. …”

“…Written by Eyal Wirsansky, a senior data scientist and AI researcher with over 25 years of experience and a research background in genetic algorithms and neural networks, Hands-On Genetic Algorithms with Python offers expert insights and practical knowledge to master genetic algorithms. …”

Tabla de Contenidos: “…-- When a process requires a procedure -- How to write a procedure -- Step 1: gathering information -- Step 2: beginning to write -- Step 3: evaluating design elements -- Summary -- Chapter 9: Social Engineering, Password Guidance, and Policy -- The starting point -- OSINT -- Social scientist -- Common social engineering attack methods -- Pretexting -- Misdirection theft -- Phishing -- Targeted phishing -- Vishing -- Smishing -- Have you got a M.A.P.P.? …”

Tabla de Contenidos: “…Cover -- Title Page -- Copyright -- Dedication -- Contents -- Preface -- Chapter 1 Introduction: Becoming a Unicorn -- 1.1 Aren't Data Scientists Just Overpaid Statisticians? -- 1.2 How Is This Book Organized? …”