TensorFlow Developer Certification Guide PDF Download
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Author: Patrick J
Publisher: GitforGits
ISBN: 8119177746
Category : Computers
Languages : en
Pages : 296
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Book Description
Designed with both beginners and professionals in mind, the book is meticulously structured to cover a broad spectrum of concepts, applications, and hands-on practices that form the core of the TensorFlow Developer Certificate exam. Starting with foundational concepts, the book guides you through the fundamental aspects of TensorFlow, Machine Learning algorithms, and Deep Learning models. The initial chapters focus on data preprocessing, exploratory analysis, and essential tools required for building robust models. The book then delves into Convolutional Neural Networks (CNNs), Long Short-Term Memory Networks (LSTMs), and advanced neural network techniques such as GANs and Transformer Architecture. Emphasizing practical application, each chapter is peppered with detailed explanations, code snippets, and real-world examples, allowing you to apply the concepts in various domains such as text classification, sentiment analysis, object detection, and more. A distinctive feature of the book is its focus on various optimization and regularization techniques that enhance model performance. As the book progresses, it navigates through the complexities of deploying TensorFlow models into production. It includes exhaustive sections on TensorFlow Serving, Kubernetes Cluster, and edge computing with TensorFlow Lite. The book provides practical insights into monitoring, updating, and handling possible errors in production, ensuring a smooth transition from development to deployment. The final chapters are devoted to preparing you for the TensorFlow Developer Certificate exam. From strategies, tips, and coding challenges to a summary of the entire learning journey, these sections serve as a robust toolkit for exam readiness. With hints and solutions provided for challenges, you can assess your knowledge and fine-tune your problem solving skills. In essence, this book is more than a mere certification guide; it's a complete roadmap to mastering TensorFlow. It aligns perfectly with the objectives of the TensorFlow Developer Certificate exam, ensuring that you are not only well-versed in the theoretical aspects but are also skilled in practical applications. Key Learnings Comprehensive guide to TensorFlow, covering fundamentals to advanced topics, aiding seamless learning. Alignment with TensorFlow Developer Certificate exam, providing targeted preparation and confidence. In-depth exploration of neural networks, enhancing understanding of model architecture and function. Hands-on examples throughout, ensuring practical understanding and immediate applicability of concepts. Detailed insights into model optimization, including regularization, boosting model performance. Extensive focus on deployment, from TensorFlow Serving to Kubernetes, for real-world applications. Exploration of innovative technologies like BiLSTM, attention mechanisms, Transformers, fostering creativity. Step-by-step coding challenges, enhancing problem-solving skills, mirroring real-world scenarios. Coverage of potential errors in deployment, offering practical solutions, ensuring robust applications. Continual emphasis on practical, applicable knowledge, making it suitable for all levels Table of Contents Introduction to Machine Learning and TensorFlow 2.x Up and Running with Neural Networks Building Basic Machine Learning Models Image Recognition with CNN Object Detection Algorithms Text Recognition and Natural Language Processing Strategies to Prevent Overfitting & Underfitting Advanced Neural Networks for NLP Productionizing TensorFlow Models Preparing for TensorFlow Developer Certificate Exam
Author: Patrick J
Publisher: GitforGits
ISBN: 8119177746
Category : Computers
Languages : en
Pages : 296
Get Book Here
Book Description
Designed with both beginners and professionals in mind, the book is meticulously structured to cover a broad spectrum of concepts, applications, and hands-on practices that form the core of the TensorFlow Developer Certificate exam. Starting with foundational concepts, the book guides you through the fundamental aspects of TensorFlow, Machine Learning algorithms, and Deep Learning models. The initial chapters focus on data preprocessing, exploratory analysis, and essential tools required for building robust models. The book then delves into Convolutional Neural Networks (CNNs), Long Short-Term Memory Networks (LSTMs), and advanced neural network techniques such as GANs and Transformer Architecture. Emphasizing practical application, each chapter is peppered with detailed explanations, code snippets, and real-world examples, allowing you to apply the concepts in various domains such as text classification, sentiment analysis, object detection, and more. A distinctive feature of the book is its focus on various optimization and regularization techniques that enhance model performance. As the book progresses, it navigates through the complexities of deploying TensorFlow models into production. It includes exhaustive sections on TensorFlow Serving, Kubernetes Cluster, and edge computing with TensorFlow Lite. The book provides practical insights into monitoring, updating, and handling possible errors in production, ensuring a smooth transition from development to deployment. The final chapters are devoted to preparing you for the TensorFlow Developer Certificate exam. From strategies, tips, and coding challenges to a summary of the entire learning journey, these sections serve as a robust toolkit for exam readiness. With hints and solutions provided for challenges, you can assess your knowledge and fine-tune your problem solving skills. In essence, this book is more than a mere certification guide; it's a complete roadmap to mastering TensorFlow. It aligns perfectly with the objectives of the TensorFlow Developer Certificate exam, ensuring that you are not only well-versed in the theoretical aspects but are also skilled in practical applications. Key Learnings Comprehensive guide to TensorFlow, covering fundamentals to advanced topics, aiding seamless learning. Alignment with TensorFlow Developer Certificate exam, providing targeted preparation and confidence. In-depth exploration of neural networks, enhancing understanding of model architecture and function. Hands-on examples throughout, ensuring practical understanding and immediate applicability of concepts. Detailed insights into model optimization, including regularization, boosting model performance. Extensive focus on deployment, from TensorFlow Serving to Kubernetes, for real-world applications. Exploration of innovative technologies like BiLSTM, attention mechanisms, Transformers, fostering creativity. Step-by-step coding challenges, enhancing problem-solving skills, mirroring real-world scenarios. Coverage of potential errors in deployment, offering practical solutions, ensuring robust applications. Continual emphasis on practical, applicable knowledge, making it suitable for all levels Table of Contents Introduction to Machine Learning and TensorFlow 2.x Up and Running with Neural Networks Building Basic Machine Learning Models Image Recognition with CNN Object Detection Algorithms Text Recognition and Natural Language Processing Strategies to Prevent Overfitting & Underfitting Advanced Neural Networks for NLP Productionizing TensorFlow Models Preparing for TensorFlow Developer Certificate Exam
Author: Oluwole Fagbohun
Publisher: Packt Publishing Ltd
ISBN: 180324920X
Category : Computers
Languages : en
Pages : 350
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Book Description
Achieve TensorFlow certification with this comprehensive guide covering all exam topics using a hands-on, step-by-step approach—perfect for aspiring TensorFlow developers Key Features Build real-world computer vision, natural language, and time series applications Learn how to overcome issues such as overfitting with techniques such as data augmentation Master transfer learning—what it is and how to build applications with pre-trained models Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThe TensorFlow Developer Certificate Guide is an indispensable resource for machine learning enthusiasts and data professionals seeking to master TensorFlow and validate their skills by earning the certification. This practical guide equips you with the skills and knowledge necessary to build robust deep learning models that effectively tackle real-world challenges across diverse industries. You’ll embark on a journey of skill acquisition through easy-to-follow, step-by-step explanations and practical examples, mastering the craft of building sophisticated models using TensorFlow 2.x and overcoming common hurdles such as overfitting and data augmentation. With this book, you’ll discover a wide range of practical applications, including computer vision, natural language processing, and time series prediction. To prepare you for the TensorFlow Developer Certificate exam, it offers comprehensive coverage of exam topics, including image classification, natural language processing (NLP), and time series analysis. With the TensorFlow certification, you’ll be primed to tackle a broad spectrum of business problems and advance your career in the exciting field of machine learning. Whether you are a novice or an experienced developer, this guide will propel you to achieve your aspirations and become a highly skilled TensorFlow professional. What you will learn Prepare for success in the TensorFlow Developer Certification exam Master regression and classification modelling with TensorFlow 2.x Build, train, evaluate, and fine-tune deep learning models Combat overfitting using techniques such as dropout and data augmentation Classify images, encompassing preprocessing and image data augmentation Apply TensorFlow for NLP tasks like text classification and generation Predict time series data, such as stock prices Explore real-world case studies and engage in hands-on exercises Who this book is forThis book is for machine learning and data science enthusiasts, as well as data professionals aiming to demonstrate their expertise in building deep learning applications with TensorFlow. Through a comprehensive hands-on approach, this book covers all the essential exam prerequisites to equip you with the skills needed to excel as a TensorFlow developer and advance your career in machine learning. A fundamental grasp of Python programming is the only prerequisite.
Author: Jayant Deshmukh
Publisher: Jayant Deshmukh
ISBN:
Category : Computers
Languages : en
Pages : 105
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Book Description
Building a Career in AI: A Practical Guide for Aspiring Professionals Artificial intelligence is reshaping industries, creating new opportunities, and revolutionizing the way we work and live. Are you ready to become part of this transformation? Whether you're a student curious about AI or a professional considering a career shift, this book is your ultimate guide to building a rewarding career in one of the most dynamic fields of our time. Written by Jayant Deshmukh, a Certified Project Management Professional (PMP), accomplished AI practitioner, and seasoned leader in digital transformation, this book combines deep expertise with a human touch. Jayant has worked with top global financial institutions, orchestrating transformative AI-driven initiatives, and has traveled extensively, gaining unique insights into diverse cultures, industries, and challenges. With this wealth of experience, he delivers an engaging and practical roadmap tailored for aspiring AI professionals. What This Book Offers This isn’t just another technical manual—it’s a hands-on, inspiring journey into the world of AI. Building a Career in AI demystifies complex concepts and equips you with the tools, skills, and strategies you need to succeed. A Beginner-Friendly Approach: Complex AI terms like machine learning, neural networks, and data science are explained in simple, relatable language, making them accessible even to those new to technology. Step-by-Step Guidance: Learn how to acquire essential skills like Python programming, mathematics, and domain knowledge. Follow clear roadmaps to build your expertise, whether you're starting from scratch or transitioning from another field. Practical Resources: Discover the best online courses, books, certifications, and tools to enhance your learning. Get insights into platforms like TensorFlow, PyTorch, and Kaggle, and learn how to build a portfolio of AI projects that stand out. Real-Life Stories: Be inspired by the journeys of individuals who started with no technical background but successfully transitioned into AI careers. From college graduates to mid-career professionals, these stories prove that success in AI is achievable for anyone with determination. Career Strategies: Master the art of building a personal brand through LinkedIn, GitHub, and Kaggle. Gain insider tips for crafting resumes, acing interviews, and presenting your projects effectively. Future-Proofing Your Career: Stay updated with emerging trends like generative AI, and learn how to evolve into leadership roles, from practitioner to strategist. Why This Book Matters The field of AI is rapidly growing, with a global demand for skilled professionals outpacing supply. This creates unparalleled opportunities for those who are prepared. However, starting your journey can feel overwhelming. This book bridges the gap, providing a clear, actionable framework to help you navigate the AI landscape with confidence. Jayant’s unique perspective—combining technical expertise, global industry experience, and an empathetic understanding of aspiring professionals’ challenges—ensures that every chapter is both practical and inspiring. His engaging storytelling, combined with motivational quotes and interactive exercises, makes this book more than a guide; it’s a mentor on your AI journey. Who Should Read This Book Students: If you’re in college and curious about AI, this book will guide you through building foundational skills, exploring career paths, and preparing for the job market. Professionals: If you’re looking to transition into AI from another field, you’ll find step-by-step strategies and inspiring examples to help you pivot successfully. Aspiring Innovators: If you dream of leveraging AI to create meaningful solutions, this book will equip you with the mindset, tools, and knowledge to make an impact. Start Your AI Journey Today The future belongs to those who embrace change and seize new opportunities. With Building a Career in AI, you’ll gain not only technical knowledge but also the confidence and motivation to take the first step—and every step after—toward a fulfilling career in AI. "The only limit to our realization of tomorrow will be our doubts of today." — Franklin D. Roosevelt This is more than a book; it’s your companion in navigating the exciting and ever-evolving world of artificial intelligence. Whether you’re starting small or dreaming big, your journey begins here. Take the leap, embrace the possibilities, and let this book guide you to a future shaped by your potential and the limitless power of AI. Are you ready to build your career in AI? The time is now!
Author: Cybellium
Publisher: Cybellium Ltd
ISBN: 1836798067
Category : Computers
Languages : en
Pages : 242
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Book Description
Designed for professionals, students, and enthusiasts alike, our comprehensive books empower you to stay ahead in a rapidly evolving digital world. * Expert Insights: Our books provide deep, actionable insights that bridge the gap between theory and practical application. * Up-to-Date Content: Stay current with the latest advancements, trends, and best practices in IT, Al, Cybersecurity, Business, Economics and Science. Each guide is regularly updated to reflect the newest developments and challenges. * Comprehensive Coverage: Whether you're a beginner or an advanced learner, Cybellium books cover a wide range of topics, from foundational principles to specialized knowledge, tailored to your level of expertise. Become part of a global network of learners and professionals who trust Cybellium to guide their educational journey. www.cybellium.com
Author: Cybellium Ltd
Publisher: Cybellium Ltd
ISBN:
Category : Computers
Languages : en
Pages : 198
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Book Description
Google Certification Guide - Google Professional Cloud Developer Master Cloud Development on Google Cloud Embark on a transformative journey into cloud development with Google Cloud through this in-depth guide, tailored for those aspiring to become Google Professional Cloud Developers. This comprehensive resource is your key to mastering the development of scalable, reliable, and efficient cloud-native applications using Google Cloud services. Inside This Guide, You Will Discover: In-Depth Development Concepts: Explore the essentials of Google Cloud development, including services like App Engine, Kubernetes Engine, and Cloud Functions. Hands-On Application: Engage with practical examples and real-world projects that demonstrate effective cloud development practices and solutions on Google Cloud. Exam-Focused Preparation: Detailed insights into the exam structure and content, complete with targeted study tips and practice questions, to ensure thorough preparation. Latest Cloud Development Trends: Stay current with the evolving landscape of Google Cloud, learning how to leverage new features and best practices in cloud development. Crafted by an Expert in Cloud Development Authored by a seasoned cloud developer with extensive experience in Google Cloud technologies, this guide merges technical expertise with practical insights, offering a comprehensive learning experience. Your Comprehensive Resource for Cloud Developer Certification Whether you're new to cloud development or an experienced developer aiming to validate your Google Cloud skills, this book is an invaluable companion, guiding you through the complexities of Google Cloud development and preparing you for the Professional Cloud Developer certification. Elevate Your Cloud Development Skills Go beyond the basics and gain a deep, practical understanding of developing applications on Google Cloud. This guide is more than a pathway to certification; it's a blueprint for excelling in cloud development. Begin Your Cloud Development Adventure Start your journey to becoming a certified Google Professional Cloud Developer. With this guide, you're not just preparing for an exam; you're preparing to become a skilled architect of innovative cloud solutions. © 2023 Cybellium Ltd. All rights reserved. www.cybellium.com
Author: Konrad Cłapa
Publisher: Packt Publishing Ltd
ISBN: 1838553525
Category : Computers
Languages : en
Pages : 504
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Book Description
Become a Professional Cloud Architect by exploring essential concepts, tools, and services in GCP and working through tests designed to help you get certified Key FeaturesPlan and design a GCP cloud solution architectureEnsure the security and reliability of your cloud solutions and operationsTest yourself by taking mock tests with up-to-date exam questionsBook Description Google Cloud Platform (GCP) is one of the leading cloud service suites and offers solutions for storage, analytics, big data, machine learning, and application development. It features an array of services that can help organizations to get the best out of their infrastructure. This comprehensive guide covers a variety of topics specific to Google's Professional Cloud Architect official exam syllabus and guides you in using the right methods for effective use of GCP services. You'll start by exploring GCP, understanding the benefits of becoming a certified architect, and learning how to register for the exam. You'll then delve into the core services that GCP offers such as computing, storage, and security. As you advance, this GCP book will help you get up to speed with methods to scale and automate your cloud infrastructure and delve into containers and services. In the concluding chapters, you'll discover security best practices and even gain insights into designing applications with GCP services and monitoring your infrastructure as a GCP architect. By the end of this book, you will be well versed in all the topics required to pass Google's Professional Cloud Architect exam and use GCP services effectively. What you will learnManage your GCP infrastructure with Google Cloud management options such as CloudShell and SDKUnderstand the use cases for different storage optionsDesign a solution with security and compliance in mindMonitor GCP compute optionsDiscover machine learning and the different machine learning models offered by GCPUnderstand what services need to be used when planning and designing your architectureWho this book is for If you are a cloud architect, cloud engineer, administrator, or any IT professional who wants to learn how to implement Google Cloud services in your organization and become a GCP Certified Professional Cloud Architect, this book is for you. Basic knowledge of server infrastructure, including Linux and Windows Servers, is assumed. Knowledge of network and storage will also be helpful.
Author: Luciano Ramalho
Publisher: "O'Reilly Media, Inc."
ISBN: 1491946253
Category : Computers
Languages : en
Pages : 755
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Book Description
Python’s simplicity lets you become productive quickly, but this often means you aren’t using everything it has to offer. With this hands-on guide, you’ll learn how to write effective, idiomatic Python code by leveraging its best—and possibly most neglected—features. Author Luciano Ramalho takes you through Python’s core language features and libraries, and shows you how to make your code shorter, faster, and more readable at the same time. Many experienced programmers try to bend Python to fit patterns they learned from other languages, and never discover Python features outside of their experience. With this book, those Python programmers will thoroughly learn how to become proficient in Python 3. This book covers: Python data model: understand how special methods are the key to the consistent behavior of objects Data structures: take full advantage of built-in types, and understand the text vs bytes duality in the Unicode age Functions as objects: view Python functions as first-class objects, and understand how this affects popular design patterns Object-oriented idioms: build classes by learning about references, mutability, interfaces, operator overloading, and multiple inheritance Control flow: leverage context managers, generators, coroutines, and concurrency with the concurrent.futures and asyncio packages Metaprogramming: understand how properties, attribute descriptors, class decorators, and metaclasses work
Author: Jeremy Howard
Publisher: O'Reilly Media
ISBN: 1492045497
Category : Computers
Languages : en
Pages : 624
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Book Description
Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala
Author: Konrad Clapa
Publisher: Packt Publishing Ltd
ISBN: 1801811415
Category : Computers
Languages : en
Pages : 664
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Book Description
Become a Professional Cloud Architect by exploring the essential concepts, tools, and services in GCP and working through practice tests designed to help you take the exam confidently Key FeaturesPlan and design a GCP cloud solution architectureEnsure the security and reliability of your cloud solutions and operationsAssess your knowledge by taking mock tests with up-to-date exam questionsBook Description Google Cloud Platform (GCP) is one of the industry leaders thanks to its array of services that can be leveraged by organizations to bring the best out of their infrastructure. This book is a comprehensive guide for learning methods to effectively utilize GCP services and help you become acquainted with the topics required to pass Google's Professional Cloud Architect certification exam. Following the Professional Cloud Architect's official exam syllabus, you'll first be introduced to the GCP. The book then covers the core services that GCP offers, such as computing and storage, and takes you through effective methods of scaling and automating your cloud infrastructure. As you progress through the chapters, you'll get to grips with containers and services and discover best practices related to the design and process. This revised second edition features new topics such as Cloud Run, Anthos, Data Fusion, Composer, and Data Catalog. By the end of this book, you'll have gained the knowledge required to take and pass the Google Cloud Certification – Professional Cloud Architect exam and become an expert in GCP services. What you will learnUnderstand the benefits of being a Google Certified Professional Cloud ArchitectFind out how to enroll for the Professional Cloud Architect examMaster the compute options in GCPExplore security and networking options in GCPGet to grips with managing and monitoring your workloads in GCPUnderstand storage, big data, and machine learning servicesBecome familiar with exam scenarios and passing strategiesWho this book is for If you are a cloud architect, cloud engineer, administrator, or any IT professional looking to learn how to implement Google Cloud services in your organization and become a GCP Certified Professional Cloud Architect, this book is for you. Basic knowledge of server infrastructure, including Linux and Windows Servers, is assumed. A solid understanding of network and storage will help you to make the most out of this book.
Author: Mattmann A. Chris
Publisher: Manning
ISBN: 1617297712
Category : Computers
Languages : en
Pages : 454
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Book Description
Updated with new code, new projects, and new chapters, Machine Learning with TensorFlow, Second Edition gives readers a solid foundation in machine-learning concepts and the TensorFlow library. Summary Updated with new code, new projects, and new chapters, Machine Learning with TensorFlow, Second Edition gives readers a solid foundation in machine-learning concepts and the TensorFlow library. Written by NASA JPL Deputy CTO and Principal Data Scientist Chris Mattmann, all examples are accompanied by downloadable Jupyter Notebooks for a hands-on experience coding TensorFlow with Python. New and revised content expands coverage of core machine learning algorithms, and advancements in neural networks such as VGG-Face facial identification classifiers and deep speech classifiers. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Supercharge your data analysis with machine learning! ML algorithms automatically improve as they process data, so results get better over time. You don’t have to be a mathematician to use ML: Tools like Google’s TensorFlow library help with complex calculations so you can focus on getting the answers you need. About the book Machine Learning with TensorFlow, Second Edition is a fully revised guide to building machine learning models using Python and TensorFlow. You’ll apply core ML concepts to real-world challenges, such as sentiment analysis, text classification, and image recognition. Hands-on examples illustrate neural network techniques for deep speech processing, facial identification, and auto-encoding with CIFAR-10. What's inside Machine Learning with TensorFlow Choosing the best ML approaches Visualizing algorithms with TensorBoard Sharing results with collaborators Running models in Docker About the reader Requires intermediate Python skills and knowledge of general algebraic concepts like vectors and matrices. Examples use the super-stable 1.15.x branch of TensorFlow and TensorFlow 2.x. About the author Chris Mattmann is the Division Manager of the Artificial Intelligence, Analytics, and Innovation Organization at NASA Jet Propulsion Lab. The first edition of this book was written by Nishant Shukla with Kenneth Fricklas. Table of Contents PART 1 - YOUR MACHINE-LEARNING RIG 1 A machine-learning odyssey 2 TensorFlow essentials PART 2 - CORE LEARNING ALGORITHMS 3 Linear regression and beyond 4 Using regression for call-center volume prediction 5 A gentle introduction to classification 6 Sentiment classification: Large movie-review dataset 7 Automatically clustering data 8 Inferring user activity from Android accelerometer data 9 Hidden Markov models 10 Part-of-speech tagging and word-sense disambiguation PART 3 - THE NEURAL NETWORK PARADIGM 11 A peek into autoencoders 12 Applying autoencoders: The CIFAR-10 image dataset 13 Reinforcement learning 14 Convolutional neural networks 15 Building a real-world CNN: VGG-Face ad VGG-Face Lite 16 Recurrent neural networks 17 LSTMs and automatic speech recognition 18 Sequence-to-sequence models for chatbots 19 Utility landscape
