The Machine Learning Solutions Architect Handbook. Create machine learning platforms to run solutions in an enterprise setting

David Ping

When equipped with a highly scalable machine learning (ML) platform, organizations can quickly scale the delivery of ML products for faster business value realization. There is a huge demand for skilled ML solutions architects in different industries, and this handbook will help you master the design patterns, architectural considerations, and the latest technology insights you’ll need to become one. You’ll start by understanding ML fundamentals and how ML can be applied to solve real-world business problems. Once you've explored a few leading problem-solving ML algorithms, this book will help you tackle data management and get the most out of ML libraries such as TensorFlow and PyTorch. Using open source technology such as Kubernetes/Kubeflow to build a data science environment and ML pipelines will be covered next, before moving on to building an enterprise ML architecture using Amazon Web Services (AWS). You’ll also learn about security and governance considerations, advanced ML engineering techniques, and how to apply bias detection, explainability, and privacy in ML model development. And finally, you'll get acquainted with AWS AI services and their applications in real-world use cases.By the end of this book, you’ll be able to design and build an ML platform to support common use cases and architecture patterns like a true professional.

CiviCRM Cookbook. Improve your CiviCRM capabilities with this clever cookbook. Packed with recipes and screenshots, it's the natural way to dig deeper into the software and achieve more for your nonprofit or civic sector organization

ANTHONY HORROCKS, Dave Greenberg

CiviCRM is a web-based, open source, Constituent Relationship Management (CRM) software geared toward meeting the needs of non-profit and other civic-sector organizations.Organizations realize their mission via CiviCRM through contact management, fundraising, event management, member management, mass e-mail marketing, peer-to-peer campaigns, case management, and much more.CiviCRM is localized in over 20 languages including: Chinese (Taiwan, China), Dutch, English (Australia, Canada, U.S., UK), French (France, Canada), German, Italian, Japanese, Russian, and Swedish.CiviCRM Cookbook will enhance your CiviCRM skills. It has recipes to help you use CiviCRM more efficiently, integrate it with CMSs, and also develop CiviCRM.This book begins with recipes that help save time and effort with CiviCRM. This is followed by recipes for organizing data more efficiently and managing profiles.Then you will learn authentication and authorization and managing communication with contacts.Then you will be guided on using the searching feature and preparing reports. We will then talk about integrating Drupal and CiviCRM. You will also be taught to manage events effectively. Finally, learn about CiviCampaign, Civimember, and developing CiviCRM.

Learning Cocos2d-x Game Development. Learn cross-platform game development with Cocos2d-x

Siddharth Shekar

Scala: Guide for Data Science Professionals. Build robust data pipelines with Scala

Arun Manivannan, Pascal Bugnion, Patrick R. Nicolas

Scala is especially good for analyzing large sets of data as the scale of the task doesn’t have any significant impact on performance. Scala’s powerful functional libraries can interact with databases and build scalable frameworks — resulting in the creation of robust data pipelines. The first module introduces you to Scala libraries to ingest, store, manipulate, process, and visualize data. Using real world examples, you will learn how to design scalable architecture to process and model data — starting from simple concurrency constructs and progressing to actor systems and Apache Spark. After this, you will also learn how to build interactive visualizations with web frameworks.Once you have become familiar with all the tasks involved in data science, you will explore data analytics with Scala in the second module. You’ll see how Scala can be used to make sense of data through easy to follow recipes. You will learn about Bokeh bindings for exploratory data analysis and quintessential machine learning with algorithms with Spark ML library. You’ll get a sufficient understanding of Spark streaming, machine learning for streaming data, and Spark graphX. Armed with a firm understanding of data analysis, you will be ready to explore the most cutting-edge aspect of data science — machine learning. The final module teaches you the A to Z of machine learning with Scala. You’ll explore Scala for dependency injections and implicits, which are used to write machine learning algorithms. You’ll also explore machine learning topics such as clustering, dimentionality reduction, Naïve Bayes, Regression models, SVMs, neural networks, and more. This learning path combines some of the best that Packt has to offer into one complete, curated package. It includes content from the following Packt products:• Scala for Data Science, Pascal Bugnion• Scala Data Analysis Cookbook, Arun Manivannan • Scala for Machine Learning, Patrick R. Nicolas

Moodle Gradebook. If you’re already using Moodle for your courses, adding the power of the in-built gradebook can make teaching life a lot easier. This book tells you all about it – from basic concepts to clever customization

Rebecca Barrington

Moodle, as a learning management system, is used to provide resources, interactive activities and assessments to students. Through the use of the gradebook, Moodle can also be used to store grades, calculate final marks and track student achievement and progress to help the teacher manage the learning process.Through the use of the gradebook, Moodle can also be used to store grades, making it much easier for you to organize your work and relay information to your students. This book provides examples of practical uses of the gradebook to demystify the terminology and options available, allowing you to make full use of the assessment tracking features and, most importantly, customize it to meet your needs. Moodle Gradebook will introduce you to the core functions of the gradebook as you will learn how to add your own graded activities before marking this work. You will customize how you view the grades and organize the activities so that your course needs are met. You will also use the new completion functions within Moodle 2.x to track progress further. Make the gradebook accommodate your requirements by adding your own grading options and setting it up to present the information you need.

Big Data Analytics. Real time analytics using Apache Spark and Hadoop

Venkat Ankam

Big Data Analytics book aims at providing the fundamentals of Apache Spark and Hadoop. All Spark components – Spark Core, Spark SQL, DataFrames, Data sets, Conventional Streaming, Structured Streaming, MLlib, Graphx and Hadoop core components – HDFS, MapReduce and Yarn are explored in greater depth with implementation examples on Spark + Hadoop clusters. It is moving away from MapReduce to Spark. So, advantages of Spark over MapReduce are explained at great depth to reap benefits of in-memory speeds. DataFrames API, Data Sources API and new Data set API are explained for building Big Data analytical applications. Real-time data analytics using Spark Streaming with Apache Kafka and HBase is covered to help building streaming applications. New Structured streaming concept is explained with an IOT (Internet of Things) use case. Machine learning techniques are covered using MLLib, ML Pipelines and SparkR and Graph Analytics are covered with GraphX and GraphFrames components of Spark. Readers will also get an opportunity to get started with web based notebooks such as Jupyter, Apache Zeppelin and data flow tool Apache NiFi to analyze and visualize data.

React Anti-Patterns. Build efficient and maintainable React applications with test-driven development and refactoring

Juntao Qiu

Take your React development skills to the next level by examining common anti-patterns with expert insights and practical solutions, to refine your codebases into sophisticated and scalable creations. Through this easy-to-follow guide, React Anti-Patterns serves as a roadmap to elevating the efficiency and maintainability of your React projects.You’ll begin by familiarizing yourself with the essential aspects of React before exploring strategies for structuring React applications and creating well-organized, modular, and easy-to-maintain codebases. From identifying and addressing common anti-patterns using refactoring techniques to harnessing the power of test-driven development (TDD), you’ll learn about the tools and techniques necessary to create reliable and robust tests. As you advance, you’ll get to grips with business logic and design patterns that offer solutions to prevalent challenges faced in React development. The book also offers insights into using composition patterns, such as code splitting and multiple entry points, to enhance the flexibility and modularity of your React applications, guiding you through end-to-end project implementation.By the end of this React book, you’ll be able to overcome common challenges and pitfalls to transform your React projects into elegant, efficient, and maintainable codebases.

Hands-On Generative Adversarial Networks with PyTorch 1.x. Implement next-generation neural networks to build powerful GAN models using Python

John Hany, Greg Walters

With continuously evolving research and development, Generative Adversarial Networks (GANs) are the next big thing in the field of deep learning. This book highlights the key improvements in GANs over generative models and guides in making the best out of GANs with the help of hands-on examples.This book starts by taking you through the core concepts necessary to understand how each component of a GAN model works. You'll build your first GAN model to understand how generator and discriminator networks function. As you advance, you'll delve into a range of examples and datasets to build a variety of GAN networks using PyTorch functionalities and services, and become well-versed with architectures, training strategies, and evaluation methods for image generation, translation, and restoration. You'll even learn how to apply GAN models to solve problems in areas such as computer vision, multimedia, 3D models, and natural language processing (NLP). The book covers how to overcome the challenges faced while building generative models from scratch. Finally, you'll also discover how to train your GAN models to generate adversarial examples to attack other CNN and GAN models.By the end of this book, you will have learned how to build, train, and optimize next-generation GAN models and use them to solve a variety of real-world problems.