50 Algorithms Every Programmer Should Know. Tackle computer science challenges with classic to modern algorithms in machine learning, software design, data systems, and cryptography - Second Edition

Imran Ahmad, Somaieh Nikpoor

The ability to use algorithms to solve real-world problems is a must-have skill for any developer or programmer. This book will help you not only to develop the skills to select and use an algorithm to tackle problems in the real world but also to understand how it works.You'll start with an introduction to algorithms and discover various algorithm design techniques, before exploring how to implement different types of algorithms, with the help of practical examples. As you advance, you'll learn about linear programming, page ranking, and graphs, and will then work with machine learning algorithms to understand the math and logic behind them.Case studies will show you how to apply these algorithms optimally before you focus on deep learning algorithms and learn about different types of deep learning models along with their practical use.You will also learn about modern sequential models and their variants, algorithms, methodologies, and architectures that are used to implement Large Language Models (LLMs) such as ChatGPT.Finally, you'll become well versed in techniques that enable parallel processing, giving you the ability to use these algorithms for compute-intensive tasks.By the end of this programming book, you'll have become adept at solving real-world computational problems by using a wide range of algorithms.

Getting Started with Kubernetes. Extend your containerization strategy by orchestrating and managing large-scale container deployments - Third Edition

Jonathan Baier, Jesse White

Kubernetes has continued to grow and achieve broad adoption across various industries, helping you to orchestrate and automate container deployments on a massive scale.Based on the recent release of Kubernetes 1.12, Getting Started with Kubernetes gives you a complete understanding of how to install a Kubernetes cluster. The book focuses on core Kubernetes constructs, such as pods, services, replica sets, replication controllers, and labels. You will understand cluster-level networking in Kubernetes, and learn to set up external access to applications running in the cluster. As you make your way through the book, you'll understand how to manage deployments and perform updates with minimal downtime. In addition to this, you will explore operational aspects of Kubernetes , such as monitoring and logging, later moving on to advanced concepts such as container security and cluster federation. You'll get to grips with integrating your build pipeline and deployments within a Kubernetes cluster, and be able to understand and interact with open source projects. In the concluding chapters, you'll orchestrate updates behind the scenes, avoid downtime on your cluster, and deal with underlying cloud provider instability within your cluster.By the end of this book, you'll have a complete understanding of the Kubernetes platform and will start deploying applications on it.

Machine Learning Automation with TPOT. Build, validate, and deploy fully automated machine learning models with Python

Dario Radečić

The automation of machine learning tasks allows developers more time to focus on the usability and reactivity of the software powered by machine learning models. TPOT is a Python automated machine learning tool used for optimizing machine learning pipelines using genetic programming. Automating machine learning with TPOT enables individuals and companies to develop production-ready machine learning models cheaper and faster than with traditional methods.With this practical guide to AutoML, developers working with Python on machine learning tasks will be able to put their knowledge to work and become productive quickly. You'll adopt a hands-on approach to learning the implementation of AutoML and associated methodologies. Complete with step-by-step explanations of essential concepts, practical examples, and self-assessment questions, this book will show you how to build automated classification and regression models and compare their performance to custom-built models. As you advance, you'll also develop state-of-the-art models using only a couple of lines of code and see how those models outperform all of your previous models on the same datasets.By the end of this book, you'll have gained the confidence to implement AutoML techniques in your organization on a production level.

Hands-On Generative Adversarial Networks with Keras. Your guide to implementing next-generation generative adversarial networks

Rafael Valle

Generative Adversarial Networks (GANs) have revolutionized the fields of machine learning and deep learning. This book will be your first step toward understanding GAN architectures and tackling the challenges involved in training them.This book opens with an introduction to deep learning and generative models and their applications in artificial intelligence (AI). You will then learn how to build, evaluate, and improve your first GAN with the help of easy-to-follow examples. The next few chapters will guide you through training a GAN model to produce and improve high-resolution images. You will also learn how to implement conditional GANs that enable you to control characteristics of GAN output. You will build on your knowledge further by exploring a new training methodology for progressive growing of GANs. Moving on, you'll gain insights into state-of-the-art models in image synthesis, speech enhancement, and natural language generation using GANs. In addition to this, you'll be able to identify GAN samples with TequilaGAN.By the end of this book, you will be well-versed with the latest advancements in the GAN framework using various examples and datasets, and you will have developed the skills you need to implement GAN architectures for several tasks and domains, including computer vision, natural language processing (NLP), and audio processing.Foreword by Ting-Chun Wang, Senior Research Scientist, NVIDIA

Django 1.0 Website Development. Build powerful web applications, quickly and cleanly, with the Django application framework

Ayman Hourieh, Jacob Kaplan-Moss, Ayman Hourieh (EUR)

Django is a high-level Python web framework that was developed by a fast-moving online-news operation to meet the stringent twin challenges of newsroom deadlines and the needs of web developers. It is designed to promote rapid development and clean, pragmatic design and lets you build high-performing, elegant web applications rapidly. Django focuses on automating as much as possible and adhering to the DRY (Don't Repeat Yourself) principle, making it easier to build high-performance web applications faster, with less code.This book will show you how to assemble Django's features and take advantage of its power to design, develop, and deploy a fully-featured web site. It will walk you through the creation of an example web application, with lots of code examples.Specially revised for version 1.0 of Django, the book starts by introducing the main design concepts in Django. Next, it leads you through the process of installing Django on your system. After that, you will start right away on building your social bookmarking application using Django. Various Django 1.0 components and sub-frameworks will be explained during this process, and you will learn about them by example.In each chapter, you will build one or more of the features that are essential in Web 2.0 applications, like user management, tags, and AJAX. You will also learn about good software development practices, such as keeping your application secure, and automating testing with unit tests. By the end of the book, you will have built a fully functional real-life Web 2.0 application, and learned how to deploy it to a production server.

OpenCL Programming by Example. A comprehensive guide on OpenCL programming with examples with this book and

Koushik Bhattacharyya, Ravishekhar Banger

Research in parallel programming has been a mainstream topic for a decade, and will continue to be so for many decades to come. Many parallel programming standards and frameworks exist, but only take into account one type of hardware architecture. Today computing platforms come with many heterogeneous devices. OpenCL provides royalty free standard to program heterogeneous hardware.This guide offers you a compact coverage of all the major topics of OpenCL programming. It explains optimization techniques and strategies in-depth, using illustrative examples and also provides case studies from diverse fields. Beginners and advanced application developers will find this book very useful.Beginning with the discussion of the OpenCL models, this book explores their architectural view, programming interfaces and primitives. It slowly demystifies the process of identifying the data and task parallelism in diverse algorithms.It presents examples from different domains to show how the problems within different domains can be solved more efficiently using OpenCL. You will learn about parallel sorting, histogram generation, JPEG compression, linear and parabolic regression and k-nearest neighborhood, a clustering algorithm in pattern recognition. Following on from this, optimization strategies are explained with matrix multiplication examples. You will also learn how to do an interoperation of OpenGL and OpenCL.OpenCL Programming by Example explains OpenCL in the simplest possible language, which beginners will find it easy to understand. Developers and programmers from different domains who want to achieve acceleration for their applications will find this book very useful.

Build Gamified Websites with PHP and jQuery. Using gaming principles to make learning more engaging, motivating, and interactive is a growing trend in web development. It's called gamification, and this book is the complete introduction to its theory and practice

Detrick DeBurr

Gamification involves the process of leveraging the features of real games into real life. A gamified website has the potential to increase user engagement, ROI, and learning. This book will help you build gamified websites with PHP and jQuery by making you understand the gamification design process to implement game mechanics in practical applications.Gamified websites are very popular amongst Internet users. The gamification of a web content draws users into action to empower them and help them develop new skills. Games engage user attention into the task and each task accomplished will mean the development and enhancement of new skills. This book will help you to apply the essence of games into real word applications such as business and education.Build Gamified Websites with PHP and jQuery aims at empowering and educating the users with an educational gamified website. The book walks through the process of developing a gamified website. Through the course of the book, you will learn gamification development process. The book emphasizes on the application of game mechanics to motivate the user. You will then use the Fogg behaviour model to influence the user behaviour. By the end of the book, you will see yourself building more engaging yet simple websites based on rational principles.

Mastering Machine Learning on AWS. Advanced machine learning in Python using SageMaker, Apache Spark, and TensorFlow

Dr. Saket S.R. Mengle, Maximo Gurmendez

Amazon Web Services (AWS) is constantly driving new innovations that empower data scientists to explore a variety of machine learning (ML) cloud services. This book is your comprehensive reference for learning and implementing advanced ML algorithms in AWS cloud.As you go through the chapters, you’ll gain insights into how these algorithms can be trained, tuned, and deployed in AWS using Apache Spark on Elastic Map Reduce (EMR), SageMaker, and TensorFlow. While you focus on algorithms such as XGBoost, linear models, factorization machines, and deep nets, the book will also provide you with an overview of AWS as well as detailed practical applications that will help you solve real-world problems. Every application includes a series of companion notebooks with all the necessary code to run on AWS. In the next few chapters, you will learn to use SageMaker and EMR Notebooks to perform a range of tasks, right from smart analytics and predictive modeling through to sentiment analysis. By the end of this book, you will be equipped with the skills you need to effectively handle machine learning projects and implement and evaluate algorithms on AWS.