Practical Simulations for Machine LearningSimulation and synthesis are core parts of the future of AI and machine learning. Consider: programmers, data scientists, and machine learning engineers can create the brain of a self-driving car without the car. Rather than use information from the real world, you can synthesize artificial data using simulations to train traditional machine learning models.That's just the beginning.
With this practical book, you'll explore the possibilities of simulation- and synthesis-based machine learning and AI, concentrating on deep reinforcement learning and imitation learning techniques. AI and ML are increasingly data driven, and simulations are a powerful, engaging way to unlock their full potential.
You'll learn how to: Design an approach for solving ML and AI problems using simulations with the Unity engine; Use a game engine to synthesize images for use as training data; Create simulation environments designed for training deep reinforcement learning and imitation learning models; Us ...
Data-Driven Alexa SkillsDesign and build innovative, custom, data-driven Alexa skills for home or business. Working through several projects, this book teaches you how to build Alexa skills and integrate them with online APIs. If you have basic Python skills, this book will show you how to build data-driven Alexa skills. You will learn to use data to give your Alexa skills dynamic intelligence, in-depth knowledge, and the ability to remember.
Data-Driven Alexa Skills takes a step-by-step approach to skill development. You will begin by configuring simple skills in the Alexa Skill Builder Console. Then you will develop advanced custom skills that use several Alexa Skill Development Kit features to integrate with lambda functions, Amazon Web Services (AWS), and Internet data feeds. These advanced skills enable you to link user accounts, query and store data using a NoSQL database, and access real estate listings and stock prices via web APIs. ...
The Azure Data Lakehouse ToolkitDesign and implement a modern data lakehouse on the Azure Data Platform using Delta Lake, Apache Spark, Azure Databricks, Azure Synapse Analytics, and Snowflake. This book teaches you the intricate details of the Data Lakehouse Paradigm and how to efficiently design a cloud-based data lakehouse using highly performant and cutting-edge Apache Spark capabilities using Azure Databricks, Azure Synapse Analytics, and Snowflake. You will learn to write efficient PySpark code for batch and streaming ELT jobs on Azure. And you will follow along with practical, scenario-based examples showing how to apply the capabilities of Delta Lake and Apache Spark to optimize performance, and secure, share, and manage a high volume, high velocity, and high variety of data in your lakehouse with ease.
The patterns of success that you acquire from reading this book will help you hone your skills to build high-performing and scalable ACID-compliant lakehouses using flexible and cost-efficient decoupled sto ...
Pro Power BI Dashboard CreationProduce high-quality, visually attractive analysis quickly and effectively with Microsoft's key BI tool. This book teaches analysts, managers, power users, and developers how to harness the power of Microsoft's self-service business intelligence flagship product to deliver compelling and interactive insight with remarkable ease. It then shows you the essential techniques needed to go from source data to dashboards that seize your audience's attention and provide them with clear and accurate information.
As well as producing elegant and visually arresting output, you learn how to enhance the user experience through adding polished interactivity. This book shows you how to make interactive dashboards that allow you to guide users through the meaning of the data that they are exploring. Drill down features are also covered that allow you and your audience to dig deeper and uncover new insights by exploring anomalous and interesting data points.
Reading this book builds your skills ...
The Enterprise Path to Service Mesh ArchitecturesPlanning to build a microservice-driven cloud native application or looking to modernize existing application services? Consider using a service mesh. A service mesh approach can help you create robust and scalable applications, but it also introduces new challenges. This updated report answers common questions regarding service mesh architectures through the lens of a large enterprise.
Author Lee Calcote, founder and CEO of Layer5, shows developers, operators, architects, and IT leaders how to evaluate your organization's readiness for using a service mesh-and provides a clear path to help you adopt one. You'll evaluate several factors when deciding which applications should be built from the ground up and which can be converted with a new service mesh architecture.
This updated edition discusses several service meshes available and the tools you need to implement them. You'll explore:
- Service mesh concepts, architecture, and components, such as control planes and data planes ...
Practical Social EngineeringEven the most advanced security teams can do little to defend against an employee clicking a malicious link, opening an email attachment, or revealing sensitive information in a phone call. Practical Social Engineering will help you better understand the techniques behind these social engineering attacks and how to thwart cyber criminals and malicious actors who use them to take advantage of human nature.
Joe Gray, an award-winning expert on social engineering, shares case studies, best practices, open source intelligence (OSINT) tools, and templates for orchestrating and reporting attacks so companies can better protect themselves. He outlines creative techniques to trick users out of their credentials, such as leveraging Python scripts and editing HTML files to clone a legitimate website. Once you've succeeded in harvesting information about your targets with advanced OSINT methods, you'll discover how to defend your own organization from similar threats.
Fast-paced, hands-on, ...
Python for Geospatial Data AnalysisIn spatial data science, things in closer proximity to one another likely have more in common than things that are farther apart. With this practical book, geospatial professionals, data scientists, business analysts, geographers, geologists, and others familiar with data analysis and visualization will learn the fundamentals of spatial data analysis to gain a deeper understanding of their data questions.
Author Bonny P. McClain demonstrates why detecting and quantifying patterns in geospatial data is vital. Both proprietary and open source platforms allow you to process and visualize spatial information. This book is for people familiar with data analysis or visualization who are eager to explore geospatial integration with Python. ...
Pro DAX and Data Modeling in Power BIDevelop powerful data models that bind data from disparate sources into a coherent whole. Then extend your data models using DAX - the query language that underpins Power BI - to create reusable measures to deliver finely-crafted custom calculations in your dashboards.
This book starts off teaching you how to define and enhance the core structures of your data model to make it a true semantic layer that transforms complex data into familiar business terms. You'll learn how to create calculated columns to solve basic analytical challenges. Then you'll move up to mastering DAX measures to finely slice and dice your data.
The book also shows how to handle temporal analysis in Power BI using a Date dimension. You will see how DAX Time Intelligence functions can simplify your analysis of data over time. Finally, the book shows how to extend DAX to filter and calculate datasets and develop DAX table functions and variables to handle complex queries. ...
Productionizing AIThis book is a guide to productionizing AI solutions using best-of-breed cloud services with workarounds to lower costs. Supplemented with step-by-step instructions covering data import through wrangling to partitioning and modeling through to inference and deployment, and augmented with plenty of Python code samples, the book has been written to accelerate the process of moving from script or notebook to app.
From an initial look at the context and ecosystem of AI solutions today, the book drills down from high-level business needs into best practices, working with stakeholders, and agile team collaboration. From there you'll explore data pipeline orchestration, machine and deep learning, including working with and finding shortcuts using artificial neural networks such as AutoML and AutoAI. You'll also learn about the increasing use of NoLo UIs through AI application development, industry case studies, and finally a practical guide to deploying containerized AI solutions.
The b ...