Tensorflow Developer Certificate Guide
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Tensorflow Developer Certificate Guide
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Author : Oluwole Fagbohun
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-09-29
Tensorflow Developer Certificate Guide written by Oluwole Fagbohun and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-29 with Computers categories.
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.
Tensorflow Developer Certification Guide
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Author : Patrick J
language : en
Publisher: GitforGits
Release Date : 2023-08-31
Tensorflow Developer Certification Guide written by Patrick J and has been published by GitforGits this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-31 with Computers categories.
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
Tensorflow Developer Certification Guide
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Author : Patrick J
language : en
Publisher: Gitforgits
Release Date : 2023-08-31
Tensorflow Developer Certification Guide written by Patrick J and has been published by Gitforgits this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-31 with categories.
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
Tensorflow Developer Certificate
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Author : Oluwole Fagbohun
language : en
Publisher: Packt Publishing
Release Date : 2023-09-29
Tensorflow Developer Certificate written by Oluwole Fagbohun and has been published by Packt Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-29 with Machine learning categories.
TensorFlow finds applications in companies like Google, Twitter, Intel, and Airbnb for solving business problems.
Practical Mlops
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Author : Noah Gift
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2021-09-14
Practical Mlops written by Noah Gift and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-14 with Computers categories.
Getting your models into production is the fundamental challenge of machine learning. MLOps offers a set of proven principles aimed at solving this problem in a reliable and automated way. This insightful guide takes you through what MLOps is (and how it differs from DevOps) and shows you how to put it into practice to operationalize your machine learning models. Current and aspiring machine learning engineers--or anyone familiar with data science and Python--will build a foundation in MLOps tools and methods (along with AutoML and monitoring and logging), then learn how to implement them in AWS, Microsoft Azure, and Google Cloud. The faster you deliver a machine learning system that works, the faster you can focus on the business problems you're trying to crack. This book gives you a head start. You'll discover how to: Apply DevOps best practices to machine learning Build production machine learning systems and maintain them Monitor, instrument, load-test, and operationalize machine learning systems Choose the correct MLOps tools for a given machine learning task Run machine learning models on a variety of platforms and devices, including mobile phones and specialized hardware
Tensorflow Developer Certificate Exam Practice Tests 2024 Made Easy
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Author : MR Troy
language : en
Publisher: MR Troy
Release Date : 2024-02-03
Tensorflow Developer Certificate Exam Practice Tests 2024 Made Easy written by MR Troy and has been published by MR Troy this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-03 with Computers categories.
What you'll learn Participants will be thoroughly prepared for the exam with tailored practice tests that closely mimic the format and content of the actual certification exam. Upon passing the exam, students will be able to add a digital badge to their LinkedIn profiles and join the TensorFlow Certificate Network. Learners will warm up hands-on experience in TensorFlow by completing practice tests and exercises in real-world scenarios. Students will regain a deep understanding of TensorFlow fundamentals, including Linear Regression, Image Classification, NLP, and Time Series predictions. Description Welcome to "TensorFlow Developer Certificate Exam Practice Tests 2024 made easy," your efficient path to mastering TensorFlow and preparing for certification. This book will equip you with the knowledge and practical skills needed for the TensorFlow Developer Certificate Exam in a convenient format. What Makes This Book Effective? Streamlined Learning: Ideal for those with busy schedules, our focused content is structured to make the most of your time (in less than 2 hours). Hands-On Practice: Dive into practice tests across key TensorFlow areas like Linear Regression, Image Classification, NLP, and Time Series, crafted to enhance your understanding and proficiency. Insider Knowledge: Gain insights with expert tips that will help you confidently approach the exam. Flexible Learning Environment: Choose your preferred learning tool-Google Colab, Jupyter Notebooks, or PyCharm-to work through the content. Why Choose This Book? Prepare with Confidence: Our carefully designed practice tests aim to give you a solid grounding in the exam's format and content areas. Join a Community: Consider joining the TensorFlow Certificate Network to connect with other professionals upon completion. Showcase Your Skills: Learn how to add a digital badge to your LinkedIn and GitHub profiles to highlight your TensorFlow capabilities. Enroll in "TensorFlow Developer Certificate Exam Practice Tests 2024 Made Easy" and start building your practical TensorFlow skills today! Who this book is for: Aspiring or current AI and machine learning professionals aiming to gain TensorFlow certification. Individuals with basic programming knowledge and/or a foundational understanding of machine learning concepts. Developers and students looking for a comprehensive yet concise preparation for the TensorFlow Developer Certificate Exam. Anyone interested in enhancing their TensorFlow skills and adding a recognized credential to their resume or online profiles. Requirements Basic understanding of any programming language (Python preferred). It's beneficial if learners have foundational knowledge of machine learning principles.
Tensorflow 2 0 Quick Start Guide
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Author : Tony Holdroyd
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-03-29
Tensorflow 2 0 Quick Start Guide written by Tony Holdroyd and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-29 with Computers categories.
Perform supervised and unsupervised machine learning and learn advanced techniques such as training neural networks. Key FeaturesTrain your own models for effective prediction, using high-level Keras API Perform supervised and unsupervised machine learning and learn advanced techniques such as training neural networksGet acquainted with some new practices introduced in TensorFlow 2.0 AlphaBook Description TensorFlow is one of the most popular machine learning frameworks in Python. With this book, you will improve your knowledge of some of the latest TensorFlow features and will be able to perform supervised and unsupervised machine learning and also train neural networks. After giving you an overview of what's new in TensorFlow 2.0 Alpha, the book moves on to setting up your machine learning environment using the TensorFlow library. You will perform popular supervised machine learning tasks using techniques such as linear regression, logistic regression, and clustering. You will get familiar with unsupervised learning for autoencoder applications. The book will also show you how to train effective neural networks using straightforward examples in a variety of different domains. By the end of the book, you will have been exposed to a large variety of machine learning and neural network TensorFlow techniques. What you will learnUse tf.Keras for fast prototyping, building, and training deep learning neural network modelsEasily convert your TensorFlow 1.12 applications to TensorFlow 2.0-compatible filesUse TensorFlow to tackle traditional supervised and unsupervised machine learning applicationsUnderstand image recognition techniques using TensorFlowPerform neural style transfer for image hybridization using a neural networkCode a recurrent neural network in TensorFlow to perform text-style generationWho this book is for Data scientists, machine learning developers, and deep learning enthusiasts looking to quickly get started with TensorFlow 2 will find this book useful. Some Python programming experience with version 3.6 or later, along with a familiarity with Jupyter notebooks will be an added advantage. Exposure to machine learning and neural network techniques would also be helpful.
Learning Tensorflow
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Author : Tom Hope. Yehezkel Resheff S.. Itay Lieder
language : en
Publisher:
Release Date : 2017
Learning Tensorflow written by Tom Hope. Yehezkel Resheff S.. Itay Lieder and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.
Machine Learning For Tensorflow
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Author : Gilberto Neal
language : en
Publisher: Independently Published
Release Date : 2025-02-22
Machine Learning For Tensorflow written by Gilberto Neal and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-22 with Computers categories.
Artificial Intelligence is transforming industries at an unprecedented pace, and TensorFlow is at the forefront of this revolution. Whether you're a beginner eager to break into AI or an experienced developer looking to refine your deep learning expertise, Mastering AI with TensorFlow is your ultimate guide to building, training, deploying, and scaling state-of-the-art machine learning models. What You'll Learn: Fundamentals of Deep Learning - Understand core AI concepts and how neural networks work. Practical Model Building - Implement CNNs, RNNs, Transformers, and GANs for real-world applications. End-to-End Deployment - Take your models from training to production using TensorFlow Serving, TensorFlow Lite, and TensorFlow.js. Natural Language Processing (NLP) - Work with Word2Vec, GPT-like models, sentiment analysis, and chatbots. AI in Industry - Learn how AI is shaping healthcare, finance, autonomous vehicles, and e-commerce. Ethics & Future Trends - Address bias, fairness, and the evolution of AI in modern society. With hands-on exercises, real-world case studies, and complete code implementations, this book ensures you gain both theoretical knowledge and practical skills. Whether you're working on cloud-based AI, federated learning, or explainable AI (XAI), you'll find step-by-step guidance to bring your AI projects to life. Don't just learn AI-master it. Get your copy today and start building the future with TensorFlow!
Beginners Guide For Tensorflow
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Author : Katie Williams Ph D
language : en
Publisher:
Release Date : 2021-03-29
Beginners Guide For Tensorflow written by Katie Williams Ph D and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-29 with categories.
Machine learning has become ubiquitous in modern society, and its applications include language translation, robotics, handwriting analysis, financial prediction, and image recognition. TensorFlow is Google's preeminent toolset for machine learning, and this hands-on guide makes it easy to understand, even for those without a background in artificial intelligence.Install TensorFlow on your computerLearn the fundamentals of statistical regression and neural networksVisualize the machine learning process with TensorBoardPerform image recognition with convolutional neural networks (CNNs)Analyze sequential data with recurrent neural networks (RNNs)Execute TensorFlow on mobile devices and the Google Cloud Platform (GCP)If you're a manager or software developer looking to use TensorFlow for machine learning, this is the book you'll want to have close by.