The Deep Learning Architects Handbook

Download The Deep Learning Architects Handbook full books in PDF, epub, and Kindle. Read online The Deep Learning Architects Handbook ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!

The Machine Learning Solutions Architect Handbook

Author : David Ping
Publisher : Packt Publishing Ltd
ISBN 13 : 1801070415
Total Pages : 442 pages
Book Rating : 4.8/5 (1 download)

DOWNLOAD NOW!

Book Synopsis The Machine Learning Solutions Architect Handbook by : David Ping

Download or read book The Machine Learning Solutions Architect Handbook written by David Ping and published by Packt Publishing Ltd. This book was released on 2022-01-21 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build highly secure and scalable machine learning platforms to support the fast-paced adoption of machine learning solutions Key Features Explore different ML tools and frameworks to solve large-scale machine learning challenges in the cloud Build an efficient data science environment for data exploration, model building, and model training Learn how to implement bias detection, privacy, and explainability in ML model development Book DescriptionWhen 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. 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. What you will learn Apply ML methodologies to solve business problems Design a practical enterprise ML platform architecture Implement MLOps for ML workflow automation Build an end-to-end data management architecture using AWS Train large-scale ML models and optimize model inference latency Create a business application using an AI service and a custom ML model Use AWS services to detect data and model bias and explain models Who this book is for This book is for data scientists, data engineers, cloud architects, and machine learning enthusiasts who want to become machine learning solutions architects. You’ll need basic knowledge of the Python programming language, AWS, linear algebra, probability, and networking concepts before you get started with this handbook.

The Deep Learning Architect's Handbook

Author : Ee Kin Chin
Publisher : Packt Publishing Ltd
ISBN 13 : 1803235349
Total Pages : 516 pages
Book Rating : 4.8/5 (32 download)

DOWNLOAD NOW!

Book Synopsis The Deep Learning Architect's Handbook by : Ee Kin Chin

Download or read book The Deep Learning Architect's Handbook written by Ee Kin Chin and published by Packt Publishing Ltd. This book was released on 2023-12-29 with total page 516 pages. Available in PDF, EPUB and Kindle. Book excerpt: Harness the power of deep learning to drive productivity and efficiency using this practical guide covering techniques and best practices for the entire deep learning life cycle Key Features Interpret your models’ decision-making process, ensuring transparency and trust in your AI-powered solutions Gain hands-on experience in every step of the deep learning life cycle Explore case studies and solutions for deploying DL models while addressing scalability, data drift, and ethical considerations Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionDeep learning enables previously unattainable feats in automation, but extracting real-world business value from it is a daunting task. This book will teach you how to build complex deep learning models and gain intuition for structuring your data to accomplish your deep learning objectives. This deep learning book explores every aspect of the deep learning life cycle, from planning and data preparation to model deployment and governance, using real-world scenarios that will take you through creating, deploying, and managing advanced solutions. You’ll also learn how to work with image, audio, text, and video data using deep learning architectures, as well as optimize and evaluate your deep learning models objectively to address issues such as bias, fairness, adversarial attacks, and model transparency. As you progress, you’ll harness the power of AI platforms to streamline the deep learning life cycle and leverage Python libraries and frameworks such as PyTorch, ONNX, Catalyst, MLFlow, Captum, Nvidia Triton, Prometheus, and Grafana to execute efficient deep learning architectures, optimize model performance, and streamline the deployment processes. You’ll also discover the transformative potential of large language models (LLMs) for a wide array of applications. By the end of this book, you'll have mastered deep learning techniques to unlock its full potential for your endeavors.What you will learn Use neural architecture search (NAS) to automate the design of artificial neural networks (ANNs) Implement recurrent neural networks (RNNs), convolutional neural networks (CNNs), BERT, transformers, and more to build your model Deal with multi-modal data drift in a production environment Evaluate the quality and bias of your models Explore techniques to protect your model from adversarial attacks Get to grips with deploying a model with DataRobot AutoML Who this book is for This book is for deep learning practitioners, data scientists, and machine learning developers who want to explore deep learning architectures to solve complex business problems. Professionals in the broader deep learning and AI space will also benefit from the insights provided, applicable across a variety of business use cases. Working knowledge of Python programming and a basic understanding of deep learning techniques is needed to get started with this book.

Solutions Architect's Handbook

Author : Saurabh Shrivastava
Publisher : Packt Publishing Ltd
ISBN 13 : 183864783X
Total Pages : 475 pages
Book Rating : 4.8/5 (386 download)

DOWNLOAD NOW!

Book Synopsis Solutions Architect's Handbook by : Saurabh Shrivastava

Download or read book Solutions Architect's Handbook written by Saurabh Shrivastava and published by Packt Publishing Ltd. This book was released on 2020-03-21 with total page 475 pages. Available in PDF, EPUB and Kindle. Book excerpt: From fundamentals and design patterns to the different strategies for creating secure and reliable architectures in AWS cloud, learn everything you need to become a successful solutions architect Key Features Create solutions and transform business requirements into technical architecture with this practical guide Understand various challenges that you might come across while refactoring or modernizing legacy applications Delve into security automation, DevOps, and validation of solution architecture Book DescriptionBecoming a solutions architect gives you the flexibility to work with cutting-edge technologies and define product strategies. This handbook takes you through the essential concepts, design principles and patterns, architectural considerations, and all the latest technology that you need to know to become a successful solutions architect. This book starts with a quick introduction to the fundamentals of solution architecture design principles and attributes that will assist you in understanding how solution architecture benefits software projects across enterprises. You'll learn what a cloud migration and application modernization framework looks like, and will use microservices, event-driven, cache-based, and serverless patterns to design robust architectures. You'll then explore the main pillars of architecture design, including performance, scalability, cost optimization, security, operational excellence, and DevOps. Additionally, you'll also learn advanced concepts relating to big data, machine learning, and the Internet of Things (IoT). Finally, you'll get to grips with the documentation of architecture design and the soft skills that are necessary to become a better solutions architect. By the end of this book, you'll have learned techniques to create an efficient architecture design that meets your business requirements.What you will learn Explore the various roles of a solutions architect and their involvement in the enterprise landscape Approach big data processing, machine learning, and IoT from an architect s perspective and understand how they fit into modern architecture Discover different solution architecture patterns such as event-driven and microservice patterns Find ways to keep yourself updated with new technologies and enhance your skills Modernize legacy applications with the help of cloud integration Get to grips with choosing an appropriate strategy to reduce cost Who this book is for This book is for software developers, system engineers, DevOps engineers, architects, and team leaders working in the information technology industry who aspire to become solutions architect professionals. A good understanding of the software development process and general programming experience with any language will be useful.

Big Data Architect’s Handbook

Author : Syed Muhammad Fahad Akhtar
Publisher : Packt Publishing Ltd
ISBN 13 : 1788836383
Total Pages : 476 pages
Book Rating : 4.7/5 (888 download)

DOWNLOAD NOW!

Book Synopsis Big Data Architect’s Handbook by : Syed Muhammad Fahad Akhtar

Download or read book Big Data Architect’s Handbook written by Syed Muhammad Fahad Akhtar and published by Packt Publishing Ltd. This book was released on 2018-06-21 with total page 476 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive end-to-end guide that gives hands-on practice in big data and Artificial Intelligence Key Features Learn to build and run a big data application with sample code Explore examples to implement activities that a big data architect performs Use Machine Learning and AI for structured and unstructured data Book Description The big data architects are the “masters” of data, and hold high value in today’s market. Handling big data, be it of good or bad quality, is not an easy task. The prime job for any big data architect is to build an end-to-end big data solution that integrates data from different sources and analyzes it to find useful, hidden insights. Big Data Architect’s Handbook takes you through developing a complete, end-to-end big data pipeline, which will lay the foundation for you and provide the necessary knowledge required to be an architect in big data. Right from understanding the design considerations to implementing a solid, efficient, and scalable data pipeline, this book walks you through all the essential aspects of big data. It also gives you an overview of how you can leverage the power of various big data tools such as Apache Hadoop and ElasticSearch in order to bring them together and build an efficient big data solution. By the end of this book, you will be able to build your own design system which integrates, maintains, visualizes, and monitors your data. In addition, you will have a smooth design flow in each process, putting insights in action. What you will learn Learn Hadoop Ecosystem and Apache projects Understand, compare NoSQL database and essential software architecture Cloud infrastructure design considerations for big data Explore application scenario of big data tools for daily activities Learn to analyze and visualize results to uncover valuable insights Build and run a big data application with sample code from end to end Apply Machine Learning and AI to perform big data intelligence Practice the daily activities performed by big data architects Who this book is for Big Data Architect’s Handbook is for you if you are an aspiring data professional, developer, or IT enthusiast who aims to be an all-round architect in big data. This book is your one-stop solution to enhance your knowledge and carry out easy to complex activities required to become a big data architect.

Architects of Intelligence

Author : Martin Ford
Publisher : Packt Publishing Ltd
ISBN 13 : 178913126X
Total Pages : 540 pages
Book Rating : 4.7/5 (891 download)

DOWNLOAD NOW!

Book Synopsis Architects of Intelligence by : Martin Ford

Download or read book Architects of Intelligence written by Martin Ford and published by Packt Publishing Ltd. This book was released on 2018-11-23 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt: Financial Times Best Books of the Year 2018 TechRepublic Top Books Every Techie Should Read Book Description How will AI evolve and what major innovations are on the horizon? What will its impact be on the job market, economy, and society? What is the path toward human-level machine intelligence? What should we be concerned about as artificial intelligence advances? Architects of Intelligence contains a series of in-depth, one-to-one interviews where New York Times bestselling author, Martin Ford, uncovers the truth behind these questions from some of the brightest minds in the Artificial Intelligence community. Martin has wide-ranging conversations with twenty-three of the world's foremost researchers and entrepreneurs working in AI and robotics: Demis Hassabis (DeepMind), Ray Kurzweil (Google), Geoffrey Hinton (Univ. of Toronto and Google), Rodney Brooks (Rethink Robotics), Yann LeCun (Facebook) , Fei-Fei Li (Stanford and Google), Yoshua Bengio (Univ. of Montreal), Andrew Ng (AI Fund), Daphne Koller (Stanford), Stuart Russell (UC Berkeley), Nick Bostrom (Univ. of Oxford), Barbara Grosz (Harvard), David Ferrucci (Elemental Cognition), James Manyika (McKinsey), Judea Pearl (UCLA), Josh Tenenbaum (MIT), Rana el Kaliouby (Affectiva), Daniela Rus (MIT), Jeff Dean (Google), Cynthia Breazeal (MIT), Oren Etzioni (Allen Institute for AI), Gary Marcus (NYU), and Bryan Johnson (Kernel). Martin Ford is a prominent futurist, and author of Financial Times Business Book of the Year, Rise of the Robots. He speaks at conferences and companies around the world on what AI and automation might mean for the future. Meet the minds behind the AI superpowers as they discuss the science, business and ethics of modern artificial intelligence. Read James Manyika’s thoughts on AI analytics, Geoffrey Hinton’s breakthroughs in AI programming and development, and Rana el Kaliouby’s insights into AI marketing. This AI book collects the opinions of the luminaries of the AI business, such as Stuart Russell (coauthor of the leading AI textbook), Rodney Brooks (a leader in AI robotics), Demis Hassabis (chess prodigy and mind behind AlphaGo), and Yoshua Bengio (leader in deep learning) to complete your AI education and give you an AI advantage in 2019 and the future.

Deep Learning for Computer Architects

Author : Brandon Reagen
Publisher : Springer Nature
ISBN 13 : 3031017560
Total Pages : 109 pages
Book Rating : 4.0/5 (31 download)

DOWNLOAD NOW!

Book Synopsis Deep Learning for Computer Architects by : Brandon Reagen

Download or read book Deep Learning for Computer Architects written by Brandon Reagen and published by Springer Nature. This book was released on 2022-05-31 with total page 109 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning, and specifically deep learning, has been hugely disruptive in many fields of computer science. The success of deep learning techniques in solving notoriously difficult classification and regression problems has resulted in their rapid adoption in solving real-world problems. The emergence of deep learning is widely attributed to a virtuous cycle whereby fundamental advancements in training deeper models were enabled by the availability of massive datasets and high-performance computer hardware. This text serves as a primer for computer architects in a new and rapidly evolving field. We review how machine learning has evolved since its inception in the 1960s and track the key developments leading up to the emergence of the powerful deep learning techniques that emerged in the last decade. Next we review representative workloads, including the most commonly used datasets and seminal networks across a variety of domains. In addition to discussing the workloads themselves, we also detail the most popular deep learning tools and show how aspiring practitioners can use the tools with the workloads to characterize and optimize DNNs. The remainder of the book is dedicated to the design and optimization of hardware and architectures for machine learning. As high-performance hardware was so instrumental in the success of machine learning becoming a practical solution, this chapter recounts a variety of optimizations proposed recently to further improve future designs. Finally, we present a review of recent research published in the area as well as a taxonomy to help readers understand how various contributions fall in context.

Software Architect’s Handbook

Author : Joseph Ingeno
Publisher : Packt Publishing Ltd
ISBN 13 : 1788627679
Total Pages : 584 pages
Book Rating : 4.7/5 (886 download)

DOWNLOAD NOW!

Book Synopsis Software Architect’s Handbook by : Joseph Ingeno

Download or read book Software Architect’s Handbook written by Joseph Ingeno and published by Packt Publishing Ltd. This book was released on 2018-08-30 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive guide to exploring software architecture concepts and implementing best practices Key Features Enhance your skills to grow your career as a software architect Design efficient software architectures using patterns and best practices Learn how software architecture relates to an organization as well as software development methodology Book Description The Software Architect’s Handbook is a comprehensive guide to help developers, architects, and senior programmers advance their career in the software architecture domain. This book takes you through all the important concepts, right from design principles to different considerations at various stages of your career in software architecture. The book begins by covering the fundamentals, benefits, and purpose of software architecture. You will discover how software architecture relates to an organization, followed by identifying its significant quality attributes. Once you have covered the basics, you will explore design patterns, best practices, and paradigms for efficient software development. The book discusses which factors you need to consider for performance and security enhancements. You will learn to write documentation for your architectures and make appropriate decisions when considering DevOps. In addition to this, you will explore how to design legacy applications before understanding how to create software architectures that evolve as the market, business requirements, frameworks, tools, and best practices change over time. By the end of this book, you will not only have studied software architecture concepts but also built the soft skills necessary to grow in this field. What you will learn Design software architectures using patterns and best practices Explore the different considerations for designing software architecture Discover what it takes to continuously improve as a software architect Create loosely coupled systems that can support change Understand DevOps and how it affects software architecture Integrate, refactor, and re-architect legacy applications Who this book is for The Software Architect’s Handbook is for you if you are a software architect, chief technical officer (CTO), or senior developer looking to gain a firm grasp of software architecture.

Architecture in the Age of Artificial Intelligence

Author : Neil Leach
Publisher : Bloomsbury Publishing
ISBN 13 : 1350165549
Total Pages : 281 pages
Book Rating : 4.3/5 (51 download)

DOWNLOAD NOW!

Book Synopsis Architecture in the Age of Artificial Intelligence by : Neil Leach

Download or read book Architecture in the Age of Artificial Intelligence written by Neil Leach and published by Bloomsbury Publishing. This book was released on 2021-11-18 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence is everywhere – from the apps on our phones to the algorithms of search engines. Without us noticing, the AI revolution has arrived. But what does this mean for the world of design? The first volume in a two-book series, Architecture in the Age of Artificial Intelligence introduces AI for designers and considers its positive potential for the future of architecture and design. Explaining what AI is and how it works, the book examines how different manifestations of AI will impact the discipline and profession of architecture. Highlighting current case-studies as well as near-future applications, it shows how AI is already being used as a powerful design tool, and how AI-driven information systems will soon transform the design of buildings and cities. Far-sighted, provocative and challenging, yet rooted in careful research and cautious speculation, this book, written by architect and theorist Neil Leach, is a must-read for all architects and designers – including students of architecture and all design professionals interested in keeping their practice at the cutting edge of technology.

The Architect's Handbook of Professional Practice

Author : Joseph A. Demkin
Publisher : John Wiley & Sons
ISBN 13 : 9780471419693
Total Pages : 1040 pages
Book Rating : 4.4/5 (196 download)

DOWNLOAD NOW!

Book Synopsis The Architect's Handbook of Professional Practice by : Joseph A. Demkin

Download or read book The Architect's Handbook of Professional Practice written by Joseph A. Demkin and published by John Wiley & Sons. This book was released on 2001 with total page 1040 pages. Available in PDF, EPUB and Kindle. Book excerpt: CD-ROM contains: Samples of all AIA contract documents.

PyTorch 1.x Reinforcement Learning Cookbook

Author : Yuxi (Hayden) Liu
Publisher : Packt Publishing Ltd
ISBN 13 : 1838553231
Total Pages : 334 pages
Book Rating : 4.8/5 (385 download)

DOWNLOAD NOW!

Book Synopsis PyTorch 1.x Reinforcement Learning Cookbook by : Yuxi (Hayden) Liu

Download or read book PyTorch 1.x Reinforcement Learning Cookbook written by Yuxi (Hayden) Liu and published by Packt Publishing Ltd. This book was released on 2019-10-31 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: Implement reinforcement learning techniques and algorithms with the help of real-world examples and recipes Key FeaturesUse PyTorch 1.x to design and build self-learning artificial intelligence (AI) modelsImplement RL algorithms to solve control and optimization challenges faced by data scientists todayApply modern RL libraries to simulate a controlled environment for your projectsBook Description Reinforcement learning (RL) is a branch of machine learning that has gained popularity in recent times. It allows you to train AI models that learn from their own actions and optimize their behavior. PyTorch has also emerged as the preferred tool for training RL models because of its efficiency and ease of use. With this book, you'll explore the important RL concepts and the implementation of algorithms in PyTorch 1.x. The recipes in the book, along with real-world examples, will help you master various RL techniques, such as dynamic programming, Monte Carlo simulations, temporal difference, and Q-learning. You'll also gain insights into industry-specific applications of these techniques. Later chapters will guide you through solving problems such as the multi-armed bandit problem and the cartpole problem using the multi-armed bandit algorithm and function approximation. You'll also learn how to use Deep Q-Networks to complete Atari games, along with how to effectively implement policy gradients. Finally, you'll discover how RL techniques are applied to Blackjack, Gridworld environments, internet advertising, and the Flappy Bird game. By the end of this book, you'll have developed the skills you need to implement popular RL algorithms and use RL techniques to solve real-world problems. What you will learnUse Q-learning and the state–action–reward–state–action (SARSA) algorithm to solve various Gridworld problemsDevelop a multi-armed bandit algorithm to optimize display advertisingScale up learning and control processes using Deep Q-NetworksSimulate Markov Decision Processes, OpenAI Gym environments, and other common control problemsSelect and build RL models, evaluate their performance, and optimize and deploy themUse policy gradient methods to solve continuous RL problemsWho this book is for Machine learning engineers, data scientists and AI researchers looking for quick solutions to different reinforcement learning problems will find this book useful. Although prior knowledge of machine learning concepts is required, experience with PyTorch will be useful but not necessary.

Becoming an Agile Software Architect

Author : Rajesh R V
Publisher : Packt Publishing Ltd
ISBN 13 : 1800568207
Total Pages : 372 pages
Book Rating : 4.8/5 (5 download)

DOWNLOAD NOW!

Book Synopsis Becoming an Agile Software Architect by : Rajesh R V

Download or read book Becoming an Agile Software Architect written by Rajesh R V and published by Packt Publishing Ltd. This book was released on 2021-03-19 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: A guide to successfully operating in a lean-agile organization for solutions architects and enterprise architects Key FeaturesDevelop the right combination of processes and technical excellence to address architectural challengesExplore a range of architectural techniques to modernize legacy systemsDiscover how to design and continuously improve well-architected sustainable softwareBook Description Many organizations have embraced Agile methodologies to transform their ability to rapidly respond to constantly changing customer demands. However, in this melee, many enterprises often neglect to invest in architects by presuming architecture is not an intrinsic element of Agile software development. Since the role of an architect is not pre-defined in Agile, many organizations struggle to position architects, often resulting in friction with other roles or a failure to provide a clear learning path for architects to be productive. This book guides architects and organizations through new Agile ways of incrementally developing the architecture for delivering an uninterrupted, continuous flow of values that meets customer needs. You'll explore various aspects of Agile architecture and how it differs from traditional architecture. The book later covers Agile architects' responsibilities and how architects can add significant value by positioning themselves appropriately in the Agile flow of work. Through examples, you'll also learn concepts such as architectural decision backlog,the last responsible moment, value delivery, architecting for change, DevOps, and evolutionary collaboration. By the end of this Agile book, you'll be able to operate as an architect in Agile development initiatives and successfully architect reliable software systems. What you will learnAcquire clarity on the duties of architects in Agile developmentUnderstand architectural styles such as domain-driven design and microservicesIdentify the pitfalls of traditional architecture and learn how to develop solutionsUnderstand the principles of value and data-driven architectureDiscover DevOps and continuous delivery from an architect's perspectiveAdopt Lean-Agile documentation and governanceDevelop a set of personal and interpersonal qualitiesFind out how to lead the transformation to achieve organization-wide agilityWho this book is for This agile study guide is for architects currently working on agile development projects or aspiring to work on agile software delivery, irrespective of the methodology they are using. You will also find this book useful if you're a senior developer or a budding architect looking to understand an agile architect's role by embracing agile architecture strategies and a lean-agile mindset. To understand the concepts covered in this book easily, you need to have prior knowledge of basic agile development practices.

Building Machine Learning and Deep Learning Models on Google Cloud Platform

Author : Ekaba Bisong
Publisher : Apress
ISBN 13 : 1484244702
Total Pages : 703 pages
Book Rating : 4.4/5 (842 download)

DOWNLOAD NOW!

Book Synopsis Building Machine Learning and Deep Learning Models on Google Cloud Platform by : Ekaba Bisong

Download or read book Building Machine Learning and Deep Learning Models on Google Cloud Platform written by Ekaba Bisong and published by Apress. This book was released on 2019-09-27 with total page 703 pages. Available in PDF, EPUB and Kindle. Book excerpt: Take a systematic approach to understanding the fundamentals of machine learning and deep learning from the ground up and how they are applied in practice. You will use this comprehensive guide for building and deploying learning models to address complex use cases while leveraging the computational resources of Google Cloud Platform. Author Ekaba Bisong shows you how machine learning tools and techniques are used to predict or classify events based on a set of interactions between variables known as features or attributes in a particular dataset. He teaches you how deep learning extends the machine learning algorithm of neural networks to learn complex tasks that are difficult for computers to perform, such as recognizing faces and understanding languages. And you will know how to leverage cloud computing to accelerate data science and machine learning deployments. Building Machine Learning and Deep Learning Models on Google Cloud Platform is divided into eight parts that cover the fundamentals of machine learning and deep learning, the concept of data science and cloud services, programming for data science using the Python stack, Google Cloud Platform (GCP) infrastructure and products, advanced analytics on GCP, and deploying end-to-end machine learning solution pipelines on GCP. What You’ll Learn Understand the principles and fundamentals of machine learning and deep learning, the algorithms, how to use them, when to use them, and how to interpret your resultsKnow the programming concepts relevant to machine and deep learning design and development using the Python stack Build and interpret machine and deep learning models Use Google Cloud Platform tools and services to develop and deploy large-scale machine learning and deep learning products Be aware of the different facets and design choices to consider when modeling a learning problem Productionalize machine learning models into software products Who This Book Is For Beginners to the practice of data science and applied machine learning, data scientists at all levels, machine learning engineers, Google Cloud Platform data engineers/architects, and software developers

Deep Learning Systems

Author : Andres Rodriguez
Publisher : Springer Nature
ISBN 13 : 3031017692
Total Pages : 245 pages
Book Rating : 4.0/5 (31 download)

DOWNLOAD NOW!

Book Synopsis Deep Learning Systems by : Andres Rodriguez

Download or read book Deep Learning Systems written by Andres Rodriguez and published by Springer Nature. This book was released on 2022-05-31 with total page 245 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes deep learning systems: the algorithms, compilers, and processor components to efficiently train and deploy deep learning models for commercial applications. The exponential growth in computational power is slowing at a time when the amount of compute consumed by state-of-the-art deep learning (DL) workloads is rapidly growing. Model size, serving latency, and power constraints are a significant challenge in the deployment of DL models for many applications. Therefore, it is imperative to codesign algorithms, compilers, and hardware to accelerate advances in this field with holistic system-level and algorithm solutions that improve performance, power, and efficiency. Advancing DL systems generally involves three types of engineers: (1) data scientists that utilize and develop DL algorithms in partnership with domain experts, such as medical, economic, or climate scientists; (2) hardware designers that develop specialized hardware to accelerate the components in the DL models; and (3) performance and compiler engineers that optimize software to run more efficiently on a given hardware. Hardware engineers should be aware of the characteristics and components of production and academic models likely to be adopted by industry to guide design decisions impacting future hardware. Data scientists should be aware of deployment platform constraints when designing models. Performance engineers should support optimizations across diverse models, libraries, and hardware targets. The purpose of this book is to provide a solid understanding of (1) the design, training, and applications of DL algorithms in industry; (2) the compiler techniques to map deep learning code to hardware targets; and (3) the critical hardware features that accelerate DL systems. This book aims to facilitate co-innovation for the advancement of DL systems. It is written for engineers working in one or more of these areas who seek to understand the entire system stack in order to better collaborate with engineers working in other parts of the system stack. The book details advancements and adoption of DL models in industry, explains the training and deployment process, describes the essential hardware architectural features needed for today's and future models, and details advances in DL compilers to efficiently execute algorithms across various hardware targets. Unique in this book is the holistic exposition of the entire DL system stack, the emphasis on commercial applications, and the practical techniques to design models and accelerate their performance. The author is fortunate to work with hardware, software, data scientist, and research teams across many high-technology companies with hyperscale data centers. These companies employ many of the examples and methods provided throughout the book.

Salesforce Architect's Handbook

Author : Dipanker Jyoti
Publisher : Apress
ISBN 13 : 9781484266304
Total Pages : 430 pages
Book Rating : 4.2/5 (663 download)

DOWNLOAD NOW!

Book Synopsis Salesforce Architect's Handbook by : Dipanker Jyoti

Download or read book Salesforce Architect's Handbook written by Dipanker Jyoti and published by Apress. This book was released on 2021-01-08 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: Take a deep dive into the architectural approach, best practices, and key considerations needed to comprehend, evaluate, and design an efficient, scalable, and sustainable Salesforce-based solution. This book takes a comprehensive look at the seven architectural domains that must be considered when architecting a Salesforce-based solution and equips you to develop the artifacts needed for an end-to-end enterprise architecture blueprint for Salesforce implementation and DevOps. This must-have handbook helps Salesforce professionals implement and manage Salesforce in their organization. You will learn Salesforce architecture: solution architecture, data architecture, security architecture, integration architecture, identity and access management architecture, and strategies that can be used for Salesforce-based mobile applications. In addition to the main architecture concepts, the book also offers industry best practices and the recommended framework for approaching, managing, delivering, and continuously improving a Salesforce solution using its Salesforce Development & Deployment Lifecycle. What You Will Learn Get a detailed overview of the Salesforce multi-tenant, metadata-driven architectural framework and the under-the-hood technology stack that supports Salesforce Know the seven architecture domains, their intricacies, and the considerations needed within each when designing a Salesforce solution Have an architectural mindset and the artifacts needed to architect an end-to-end enterprise-level implementation of Salesforce Be familiar with the most common Salesforce products, licenses, AppExchange products, and the key considerations of using out-of-the-box declarative capabilities vs custom programmatic capabilities of Salesforce Understand data architecture design considerations that include data modeling in Salesforce, identifying and mitigating large data volume concerns, and the key considerations for data migration and data archiving strategies Understand security architecture considerations related to securing data within Salesforce and the various approaches to allow or restrict sharing and visibility from within Salesforce Understand integration architecture considerations that provide an overview of the integration patterns and the integrations solutions that can be used with Salesforce to connect Salesforce with a remote system hosted on-premises, on the cloud, or by third-party solution providers Understand identity and access management architectural considerations across the 9 stages of an identity and access management lifecycle Be aware of the strategies available to design mobile solutions with Salesforce and the options available for Salesforce mobile architecture Employ the principles of the DevOps & Development Lifecycle needed for an ideal state Salesforce implementation Who This Book Is For Professionals interested in implementing, optimizing, and architecting Salesforce solutions enterprise-wide; Salesforce implementation (SI) partners needing a detailed playbook for architecting and delivering successful Salesforce solutions; Salesforce admins, developers, and architects looking for a one-stop educational resource to mastering the Salesforce architect domains or those pursuing the Salesforce architecture domain certification exams, including the Salesforce Certified Technical Architect (CTA) board exam

Machine Hallucinations

Author : Matias del Campo
Publisher : John Wiley & Sons
ISBN 13 : 1119748844
Total Pages : 147 pages
Book Rating : 4.1/5 (197 download)

DOWNLOAD NOW!

Book Synopsis Machine Hallucinations by : Matias del Campo

Download or read book Machine Hallucinations written by Matias del Campo and published by John Wiley & Sons. This book was released on 2022-07-13 with total page 147 pages. Available in PDF, EPUB and Kindle. Book excerpt: AI is already part of our lives even though we might not realise it. It is in our phones, filtering spam, identifying Facebook friends, and classifying our images on Instagram. It is in our homes in the form of Siri, Alexa and other AI assistants. It is in our cars and our planes. AI is literally everywhere. Artworks generated by AI have won international prizes, and have been sold at auction. But what does AI mean for the world of design? This issue of AD explores the nature of AI, and considers its potential for architecture. But this is no idle speculation. Architects have already started using AI for architectural design and fabrication. Yet – astonishingly – there has been almost no debate about AI within the discipline of architecture so far. Surely, nothing can be more important for the profession of architecture right now. The issue looks at all aspects of AI: its potential to assist architects in designing buildings so that it becomes a form of ‘augmented intelligence’; its capacity to design buildings on its own; and whether AI might open up an extraordinary new chapter in architectural design. Contributors: Refik Anadol; Daniel Bolojan; Alexa Carlson; Sofia Crespo and Feileacan McCormick; Gabriel Esquivel, Jean Jaminet and Shane Bugni; Behnaz Farahi; Theodoros Galanos and Angelos Chronis; Eduard Haiman; Wanyu He; Damjan Jovanovic and Lidija Kljakovic; Immanuel Koh; Maria Kuptsova; Sandra Manninger; Lev Manovich; Achim Menges and Thomas Wortmann; Wolf dPrix, Karolin Schmidbaur and Efilena Baseta; M Casey Rehm; and Hao Zheng and Masoud Akbarzadeh. Featured architects: Alisa Andrasek, Coop Himmelb(l)au, Lifeforms.io, Nonstandardstudio,SPAN, Kyle Steinfeld, Studio Kinch and Xkool Technology.

Handbook of Research on Emerging Trends and Applications of Machine Learning

Author : Solanki, Arun
Publisher : IGI Global
ISBN 13 : 1522596453
Total Pages : 674 pages
Book Rating : 4.5/5 (225 download)

DOWNLOAD NOW!

Book Synopsis Handbook of Research on Emerging Trends and Applications of Machine Learning by : Solanki, Arun

Download or read book Handbook of Research on Emerging Trends and Applications of Machine Learning written by Solanki, Arun and published by IGI Global. This book was released on 2019-12-13 with total page 674 pages. Available in PDF, EPUB and Kindle. Book excerpt: As today’s world continues to advance, Artificial Intelligence (AI) is a field that has become a staple of technological development and led to the advancement of numerous professional industries. An application within AI that has gained attention is machine learning. Machine learning uses statistical techniques and algorithms to give computer systems the ability to understand and its popularity has circulated through many trades. Understanding this technology and its countless implementations is pivotal for scientists and researchers across the world. The Handbook of Research on Emerging Trends and Applications of Machine Learning provides a high-level understanding of various machine learning algorithms along with modern tools and techniques using Artificial Intelligence. In addition, this book explores the critical role that machine learning plays in a variety of professional fields including healthcare, business, and computer science. While highlighting topics including image processing, predictive analytics, and smart grid management, this book is ideally designed for developers, data scientists, business analysts, information architects, finance agents, healthcare professionals, researchers, retail traders, professors, and graduate students seeking current research on the benefits, implementations, and trends of machine learning.

Salesforce B2C Solution Architect's Handbook

Author : Mike King
Publisher : Packt Publishing Ltd
ISBN 13 : 180181130X
Total Pages : 458 pages
Book Rating : 4.8/5 (18 download)

DOWNLOAD NOW!

Book Synopsis Salesforce B2C Solution Architect's Handbook by : Mike King

Download or read book Salesforce B2C Solution Architect's Handbook written by Mike King and published by Packt Publishing Ltd. This book was released on 2021-11-19 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ultimate handbook for new and seasoned Salesforce B2C Solution Architects who want to design seamless B2C solutions across the Salesforce Customer 360 ecosystem – including B2C Commerce, Service Cloud, and Marketing Cloud Key Features Give your customers a frictionless experience by creating a unified view of all their interactions Get your architectural design right the first time and avoid costly reworks Prepare for the B2C Solution Architect exam and Salesforce certification with practical scenarios following Salesforce best practices Book DescriptionThere’s a huge demand on the market for Salesforce professionals who can create a single view of the customer across the Salesforce Customer 360 platform and leverage data into actionable insights. With Salesforce B2C Solution Architect's Handbook, you’ll gain a deeper understanding of the integration options and products that help you deliver value for organizations. While this book will help you prepare for the B2C Solution Architect exam, its true value lies in setting you up for success afterwards. The first few chapters will help you develop a solid understanding of the capabilities of each component in the Customer 360 ecosystem, their data models, and governance. As you progress, you'll explore the role of a B2C solution architect in planning critical requirements and implementation sequences to avoid costly reworks and unnecessary delays. You’ll learn about the available options for integrating products with the Salesforce ecosystem and demonstrate best practices for data modeling across Salesforce products and beyond. Once you’ve mastered the core knowledge, you'll also learn about tools, techniques, and certification scenarios in preparation for the B2C Solution Architect exam. By the end of this book, you’ll have the skills to design scalable, secure, and future-proof solutions supporting critical business demands.What you will learn Explore key Customer 360 products and their integration options Choose the optimum integration architecture to unify data and experiences Architect a single view of the customer to support service, marketing, and commerce Plan for critical requirements, design decisions, and implementation sequences to avoid sub-optimal solutions Integrate Customer 360 solutions into a single-source-of-truth solution such as a master data model Support business needs that require functionality from more than one component by orchestrating data and user flows Who this book is for This book is for professionals in high-level job roles that heavily rely on Salesforce proficiency. It’s primarily written for B2C commerce architects, application architects, integration architects, as well as system architects, enterprise architects, Salesforce architects, and CTO teams looking to benefit from a deeper understanding of this platform. Before you get started, you’ll need a solid understanding of data integration, APIs, and connected systems, along with knowledge of the fundamentals of business-to-consumer (B2C) customer experiences.