Tabla de Contenidos: “…-- Chapter 48 Harness the Power of Discipline -- Chapter 49 Motivate Yourself -- Chapter 50 Derive Enjoyment from Your Profession -- Chapter 51 Think Constructively -- Chapter 52 Act Responsibly -- Chapter 53 Foster Creativity All Life Long -- Chapter 54 Assume Responsibility -- Chapter 55 Look After Yourself -- Chapter 56 Commit Yourself to More Than Just Your Own Well-Being -- Epilogue -- Bibliography -- Notes -- Index…”

Tabla de Contenidos: “…Communicating sequential processes -- PyCSP -- Processes in PyCSP -- Output -- Summary -- Chapter 9: Event-Driven Programming -- Event-driven programming -- The event loop -- Asyncio -- Getting started -- Event loops -- The run_forever() method -- The run_until_complete() method -- The stop() method -- The is_closed() method -- The close() function -- Tasks -- Example -- The all_tasks(loop=None) method -- The current_tasks() function -- The cancel() function -- Task functions -- The as_completed(fs, *, loop= -- The ensure_future(coro_or_future, *, loop= -- The wrap_future(future, *, loop= -- The gather(*coroes_or_futures, loop= -- The wait() function -- Futures -- Example -- Output -- Coroutines -- Chaining coroutines -- Output -- Transports -- Protocols -- Synchronization between coroutines -- Locks -- Queues -- Events and conditions -- Semaphores and BoundedSemaphores -- Sub-processes -- Debugging asyncio programs -- Debug mode -- Twisted -- A simple web server example -- Gevent -- Event loops -- Greenlets -- Simple example-hostnames -- Output -- Monkey patching -- Summary -- Chapter 10: Reactive Programming -- Basic reactive programming -- Maintaining purity -- ReactiveX, or RX -- Installing RxPY -- Observables -- Creating observers -- Example -- Example 2 -- Breaking it down -- Output -- Lambda functions -- Example -- Breaking it down -- On_next, on_completed, and on_error in lambda form -- Output -- Operators and chaining -- Filter example -- Breaking it down -- Chained operators -- The different operators -- Creating observables -- Transforming observables -- Filtering observables -- Error-handling observables -- Hot and cold observables -- Emitting events -- Example -- Breaking it down -- Output -- Multicasting -- Example -- Output -- Combining observables -- Zip() example -- Output -- The merge_all() operator -- Output -- Concurrency…”

Tabla de Contenidos: “…Chapter 1: Preparing Docker Hosts -- Chapter 2: Configuring Docker with Chef -- Chapter 3: Monitoring Docker -- Chapter 4: Optimizing Docker Images -- Chapter 5: Deploying Containers -- Chapter 6: Benchmarking --Chapter 7: Load Balancing -- Chapter 8: Troubleshooting Containers -- Chapter 9: Onto Production…”

Tabla de Contenidos: “…. -- See also -- Chapter 5: Exploring Testing Tools for the Validation of Azure Functions -- Introduction -- Testing Azure Functions -- Getting ready -- How to do it... -- Testing HTTP triggers using Postman -- Testing Blob trigger using the Microsoft Storage Explorer -- Testing Queue trigger using the Azure Management portal -- There's more... -- Testing an Azure Function on a staged environment using deployment slots -- How to do it... -- There's more -- Load testing Azure Functions using VSTS -- Getting ready -- How to do it... -- There's more... -- See also -- Creating and testing Azure Function locally using Azure CLI tools -- Getting ready -- How to do it... -- Testing and validating Azure Function responsiveness using Application Insights -- Getting ready -- How to do it... -- How it works... -- There's more... -- Chapter 6: Monitoring and Troubleshooting Azure Serverless Services -- Introduction -- Monitoring your Azure Functions -- Getting ready -- How to do it... -- There's more... -- Monitoring Azure Functions using Application Insights -- Getting ready -- How to do it... -- How it works... -- There's more ... -- Pushing custom telemetry details to analytics of Application Insights -- Getting ready -- How to do it... -- Creating AI function -- Configuring access keys -- Integrating and testing AI query -- Configuring the custom derived metric report -- How it works... -- See also -- Sending application telemetry details via email -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Integrating real-time AI monitoring data with Power BI using Azure Functions -- Getting ready -- How to do it... -- Configuring Power BI with dashboard, dataset, and push URI -- Creating Azure AI real-time Power BI - C# function -- How it works... -- There's more…”

“…To start with, you'll quickly run through the essential building blocks of working with an agent, programming movement, and navigation in a game environment, followed by improving your agent's decision-making and coordination mechanisms – all through hands-on examples using easily customizable techniques. …”

“…What You Will Learn Master the steps involved in the predictive modeling process Grow your expertise in using R and its diverse range of packages Learn how to classify predictive models and distinguish which models are suitable for a particular problem Understand steps for tidying data and improving the performing metrics Recognize the assumptions, strengths, and weaknesses of a predictive model Understand how and why each predictive model works in R Select appropriate metrics to assess the performance of different types of predictive model Explore word embedding and recurrent neural networks in R Train models in R that can work on very large datasets In Detail R offers a free and open source environment that is perfect for both learning and deploying predictive modeling solutions. …”

Tabla de Contenidos: “…ElasticNet -- Robust regression -- RANSAC -- Huber regression -- Bayesian regression -- Polynomial regression -- Isotonic regression -- Summary -- Chapter 5: Linear Classification Algorithms -- Linear classification -- Logistic regression -- Implementation and optimizations -- Stochastic gradient descent algorithms -- Passive-aggressive algorithms -- Passive-aggressive regression -- Finding the optimal hyperparameters through a grid search -- Classification metrics -- Confusion matrix -- Precision -- Recall -- F-Beta -- Cohen's Kappa -- Global classification report -- Learning curve -- ROC curve -- Summary -- Chapter 6: Naive Bayes and Discriminant Analysis -- Bayes' theorem -- Naive Bayes classifiers -- Naive Bayes in scikit-learn -- Bernoulli Naive Bayes -- Multinomial Naive Bayes -- An example of Multinomial Naive Bayes for text classification -- Gaussian Naive Bayes -- Discriminant analysis -- Summary -- Chapter 7: Support Vector Machines -- Linear SVM -- SVMs with scikit-learn -- Linear classification -- Kernel-based classification -- Radial Basis Function -- Polynomial kernel -- Sigmoid kernel -- Custom kernels -- Non-linear examples -- ν-Support Vector Machines -- Support Vector Regression -- An example of SVR with the Airfoil Self-Noise dataset -- Introducing semi-supervised Support Vector Machines (S3VM) -- Summary -- Chapter 8: Decision Trees and Ensemble Learning -- Binary Decision Trees -- Binary decisions -- Impurity measures -- Gini impurity index -- Cross-entropy impurity index -- Misclassification impurity index -- Feature importance -- Decision Tree classification with scikit-learn -- Decision Tree regression -- Example of Decision Tree regression with the Concrete Compressive Strength dataset -- Introduction to Ensemble Learning -- Random Forests -- Feature importance in Random Forests -- AdaBoost -- Gradient Tree Boosting…”

“…By the end of the book, you will be able to deploy Vmware NSX in your own environment with ease. This book can come handy if you are preparing for VMware NSX certification. …”

Tabla de Contenidos: “…Training the model parameters -- Evaluating model performance -- Sensitivity (Sn) -- Specificity (Sp) -- Positive predictive value (PPV) -- Negative predictive value (NPV) -- False-positive rate (FPR) -- Accuracy (Acc) -- Receiver operating characteristic (ROC) curves -- Precision-recall curves -- Continuously valued target variables -- Summary -- References and further reading -- Chapter 4: Computing Foundations - Databases -- Introduction to databases -- Data engineering with SQL - an example case -- Case details - predicting mortality for a cardiology practice -- The clinical database -- The PATIENT table -- The VISIT table -- The MEDICATIONS table -- The LABS table -- The VITALS table -- The MORT table -- Starting an SQLite session -- Data engineering, one table at a time with SQL -- Query Set #0 - creating the six tables -- Query Set #0a - creating the PATIENT table -- Query Set #0b - creating the VISIT table -- Query Set #0c - creating the MEDICATIONS table -- Query Set #0d - creating the LABS table -- Query Set #0e - creating the VITALS table -- Query Set #0f - creating the MORT table -- Query Set #0g - displaying our tables -- Query Set #1 - creating the MORT_FINAL table -- Query Set #2 - adding columns to MORT_FINAL -- Query Set #2a - adding columns using ALTER TABLE -- Query Set #2b - adding columns using JOIN -- Query Set #3 - date manipulation - calculating age -- Query Set #4 - binning and aggregating diagnoses -- Query Set #4a - binning diagnoses for CHF -- Query Set #4b - binning diagnoses for other diseases -- Query Set #4c - aggregating cardiac diagnoses using SUM -- Query Set #4d - aggregating cardiac diagnoses using COUNT -- Query Set #5 - counting medications -- Query Set #6 - binning abnormal lab results -- Query Set #7 - imputing missing variables…”

Tabla de Contenidos: “…Intro -- Copyright -- Credits -- About the Author -- About the Reviewers -- www.PacktPub.com -- Customer Feedback -- Table of Contents -- Preface -- Chapter 1: Getting Started with Android Things -- Internet of Things overview -- IoT components -- Android Things overview -- Things support library -- Android Things board compatibility -- How to install Android Things on Raspberry -- How to install Android Things using Windows -- How to install Android Things using OS X -- Testing the installation -- How to install Android Things on Intel Edison -- Configuring the WiFi -- Creating the first Android Things project -- Cloning the template project -- Create the project manually -- Differences between Android and Android Things -- Create your first Android Things app -- Summary -- Chapter 2: Creating an Alarm System Using Android Things -- Alarm system project description -- PIR sensor -- Project schematic -- How to use GPIO pins -- Reading from the GPIO pin -- How to add a listener to GPIO -- Declare the event to listen to -- Implementing the callback class -- How to close the connection with a GPIO pin -- Handle different boards in Android Things -- Android Things board pinout -- How to identify the board -- How to implement the notification system -- Configuring firebase -- Add the notification feature to the Android Things app -- Android companion app -- Summary -- Chapter 3: How to Make an Environmental Monitoring System -- Environmental monitoring system project overview -- Project components -- Project schematic -- How to read data from sensors -- Handling sensors using the Android sensor framework -- Implementing the sensor callback -- How to handle dynamic sensors -- Putting it all together - acquiring data -- How to close the sensor connection -- How to control GPIO pins -- Initialize the GPIO pin -- Diving into I2C protocol…”

“…Using the Python programming language, analysts can use these sophisticated methods to build scalable analytic applications. …”

“…What You Will Learn Understand what Infrastructure as Code (IaC) means and why it matters Install, configure, and deploy Terraform Take full control of your infrastructure in the form of code Manage complete infrastructure, starting with a single server and scaling beyond any limits Discover a great set of production-ready practices to manage infrastructure Set up CI/CD pipelines to test and deliver Terraform stacks Construct templates to simplify more complex provisioning tasks In Detail Terraform is a tool used to efficiently build, configure, and improve the production infrastructure. …”

“…What you will learn Get well-versed in blockchain basics and AI methodologies Understand the significance of data collection and cleaning in AI modeling Discover the application of analytics in cryptocurrency trading Get to grips with open, permissioned, and private blockchains Explore the DIApp design pattern and its merit in digital solutions Find out how LSTM and ARIMA can be applied in crypto trading Use the DIApp design pattern to build a sample contact tracing application Get started with building your own DIApps across various domains Who this book is for This book is for blockchain and AI architects, developers, data scientists, data engineers, and evangelists who want to harness the power of artificial intelligence in blockchain applications. …”

“…The book will introduce you to several open-source XAI tools for Python that can be used throughout the machine learning project life cycle. …”

“…To better grasp the concepts explained in this book, you must have a thorough understanding of advanced mathematical concepts, such as Markov chains, Euler's formula, and Runge-Kutta methods as the book only explains how these techniques and concepts can be implemented in Py..…”

“…By the end of The Machine Learning Workshop, you'll not only have learned the difference between supervised and unsupervised models and their applications in the real world, but you'll also have developed the skills required to get started with programming your very own machine learning algorithms. What you will learn Understand how to select an algorithm that best fits your dataset and desired outcome Explore popular real-world algorithms such as K-means, Mean-Shift, and DBSCAN Discover different approaches to solve machine learning classification problems Develop neural network structures using the scikit-learn package Use the NN algorithm to create models for predicting future outcomes Perform error analysis to improve your model's performance Who this book is for The Machine Learning Workshop is perfect for machine learning beginners. …”

“…Anyone with a working knowledge of managing identity, access, policies, updates, and apps can take this exam. Although not necessary, experience with Microsoft 365 workloads, Windows 10 devices, and non-Windows devices will be helpful…”

“…The practical concepts presented in this book can be applied in various disciplines to enhance decision-making processes with data analysis and synthesis. …”

Tabla de Contenidos: “…The Ingestion Architecture -- 5. The Role of the Data Lake -- 6. The Role of the Data Contract -- 7. …”

“…Finally, you'll explore CNN, recurrent neural network (RNN), and GAN models and their application. …”