Get started with machine learning using TensorFlow, Google's latest and greatest machine learning library. com Deep reinforcement learning is a fast-growing discipline that is making a significant impact in fields of autonomous vehicles, robotics, healthcare, finance, and many more. It's written in a casual style, which makes the flow a lot better compared to terse textbooks. by Iffat Zafar , Giounona Tzanidou , Richard Burton , Nimesh Patel , Leonardo Araujo. Dec 2, 2017 · TensorFlow: A Guide To Build Artificial Neural Networks Using Python. 192021321 This book is printed on acid-free paper in the United States of America. Author (s): Joseph Babcock, Raghav Bali. Sep 26, 2017 · The book does an acceptable (if not particularly inspired) job of walking you through the basics of TensorFlow. CH1. The book discusses the following topics. CNNs use connectivity pattern between the neurons. Sep 18, 2019 · A comprehensive guide to developing neural network-based solutions using TensorFlow 2. Explore All Courses. 6| Learning TensorFlow By Itay Lieder, Tom Hope, Yehezkel S. At the top of each tutorial, you'll see a Run in Google Colab button. Windows 7 or higher (64-bit) Purchase of the print or Kindle book includes a free PDF eBook; Book Description. First Edition. Nov 8, 2022 · Learn how to build intelligent systems with the latest tools and techniques from machine learning. May 31, 2024 · Generate text. If you have some background in basic linear algebra and calculus, this practical book introduces machine-learning fundamentals by showing you how to design systems capable of detecting objects in images, understanding text, analyzing video, and predicting Apr 13, 2024 · Caution: TensorFlow 2. Before you can build advanced models in TensorFlow 2, you will first need to understand the basics. Deep Learning with TensorFlow and Keras - Third Edition: Build and deploy supervised, unsupervised, deep, and reinforcement learning models. This book covers deep reinforcement learning using deep-q learning and policy gradient models with coding exercise. xBook DescriptionAdvanced Deep Learning May 30, 2019 · Book Description: Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. TensorFlow vs. Release date: April 2021. Our titles are available for adoption, license, or bulk purchase by institutions, corporations, etc. Using production-level tools to automate and track model training over the lifetime of a product, service, or business process is critical to success. py_func (CPU only) Chapter 3: Creating RNN, LSTM and bidirectional RNN/LSTMs with TensorFlow. Leverage the power of the Reinforcement Learning techniques to develop self-learning systems using Tensorflow About This BookLearn reinforcement learning concepts and their implementation using TensorFlow Discover different problem-solving methods …. P le a se rev ie w t h is h a nd book in it s e nt ire t y be fore re g ist e r ing a nd t a k ing t h e e xa m. Dive into deep learning with this practical course on TensorFlow and the Keras API. The book begins with an introduction to TensorFlow 2. Resheff, Itay Lieder. 1) Learn TensorFlow 2. Author (s): Chris Mattmann. It helps you to gain insight into TensorFlow Core, Keras, TF Estimators The TensorFlow platform helps you implement best practices for data automation, model tracking, performance monitoring, and model retraining. Release date: September 2019. The Machine Learning Landscape. Apr 9, 2017 · April 4, 2020. Using tf. TensorFlow has better support for distributed systems though, and has development funded by Google, while Theano is an academic project. 4) Mastering TensorFlow 1. Introduction to TensorFlow. Paolo Galeone. Sep 19, 2023 · The TensorFlow tutorials are written as Jupyter notebooks and run directly in Google Colab—a hosted notebook environment that requires no setup. Gratis. RNN unlike feed forward neural networks - can use their internal memory to process arbitrary sequences of inputs. Learn to build, train, and optimize your own networks using TensorFlow. It contains the example code and solutions to the exercises in the third edition of my O'Reilly book Hands-on Machine Learning with Scikit-Learn, Keras and TensorFlow (3rd edition): Note : If you are looking for the second edition notebooks, check out ageron/handson-ml2 . Purchase of the print or Kindle book includes a May 30, 2019 · Book Description: Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. This book is a somewhat intermediate-level introduction to Tensorflow 2. Machine Learning with TensorFlow gives readers a solid foundation in machine-learning concepts plus hands-on experience coding TensorFlow with Python. It can be used across a range of tasks but has a particular focus on training and inference of deep neural networks. 0, you'll explore a revamped framework structure, offering a wide variety of new features aimed at improving productivity and ease of use for developers. This book offers you the opportunity to grasp deep learning in an applied manner with the only requirement being an Internet connection. 0 begins with the mathematical and core technical foundations of deep learning. The 20 best tensorflow books recommended by Kirk Borne and Francois Chollet. Chapters. 3. You will use TensorFlow and OpenAI Gym to build simple neural network models that learn from their own actions. Purchase of the print or Kindle book includes a free eBook in the PDF format. Recommending a book 'Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow' by Aurélien Géron This year I started studying Artificial Intelligence at university and I wanted to get some more background on ML and practice throughout the summer as I was a complete beginner. It helps you to gain insight into TensorFlow Core, Keras, TF Estimators Updated and revised second edition of the bestselling guide to advanced deep learning with TensorFlow 2 and Keras. You'll start by getting familiar with the concepts and techniques required Title: Machine Learning Using TensorFlow Cookbook. 4) TinyML: Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers. May 10, 2019 · By Amita Kapoor and Ajit Jaokar. Sure, the book covers the MNIST and CIFAR data sets (which are the same ones you'll find discussed on the TensorFlow website), but that's not a bad thing. Après une présentation du ML, vous découvrirez le deep learning dans TensorFlow 2. The book provides a hands-on approach to TensorFlow fundamentals for a broad technical Mastering Predictive Analytics with scikit-learn and TensorFlow covers various implementations of ensemble methods, how they are used with real-world datasets, and how they improve prediction accuracy in classification and regression problems. Vous pourrez ensuite tester vos connaissances à l'aide de tutoriels de niveau débutant. Understand the basics of machine learning and discover the power of neural networks and deep learning. x: Advanced Machine learning and Deep learning concepts using TensorFlow [ check details on Amazon] Mastering TensorFlow is one of the best TensorFlow books is a comprehensive guide that lets you explore the advanced features of TensorFlow 1. x, and includes step-by-step examples using both OpenCV and TensorFlow with Python. 0 and contrast how the same code can be developed in tensorflow 2. 0Solve any deep learning problem by developing neural network-based solutions using TF 2. Here the theory of effective demand is presented for the first time, emphasizing the Release date: April 2018. May 26, 2024 · Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Edition 3 - Ebook written by Aurélien Géron. ISBN: 9781617297717. Buy Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow 2nd New edition by Geron, Aurelien (ISBN: 9781492032649) from Amazon's Book Store. Publisher (s): Packt Publishing. This book was a fantastic surface-level introduction to a vast array of machine learning methods, including their implementation in Scikit-Learn, Keras and Tensorflow (2. Roughly inspired by the human brain, deep neural networks trained with large amounts of data can solve complex tasks with unprecedented accuracy. By using concrete examples, minimal theory, and two production-ready Python frameworks-Scikit-Learn and TensorFlow-author Aurelien Geron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. 1. A Docker container runs in a virtual environment and is the easiest way to set up GPU support. x, GPU support, and Jupyter Notebooks—is provided and ready to go from Colab. CNN is a type of feed-forward artificial neural network with variations of multilayer perceptrons designed to use minimal amounts of preprocessing. Using a hands-on approach, the projects in this book will lead new programmers through the basics into developing practical deep learning applications. Work through engaging and practical deep learning projects using TensorFlow 2. 11, you will need to install TensorFlow in WSL2, or install tensorflow-cpu and, optionally, try the TensorFlow-DirectML-Plugin 1. Mar 23, 2018 · Learn how to solve challenging machine learning problems with TensorFlow, Google’s revolutionary new software library for deep learning. Click the button to open the notebook and run the code yourself. With the help of this book, you will be proficient in using TensorFlow, understand deep learning from the basics, and be able to implement machine learning algorithms in real-world scenarios. Python is a programming language that provides a wide range of features that can be used in the field of data science. Learn directly from the creator of Keras and master practical Python deep learning techniques that are easy to apply in the real world. It contains the example code and solutions to the exercises in the second edition of my O'Reilly book Hands-on Machine Learning with Scikit-Learn, Keras and TensorFlow: Note: If you are looking for the first edition notebooks, check out ageron/handson-ml. Summary. Build your own CNN models. This book shows developers how they can bring Deep learning technology to the web. Free. TensorFlow is the premier open-source deep learning framework developed and maintained by Google. Summary Hands-On Machine Learning with Scikit-Learn and TensorFlow. Kapoor, Amita (Author); English (Publication Language); 698 Pages - 10/06/2022 (Publication Date) - Packt Publishing (Publisher) $49. It builds a few different styles of models including Convolutional and Recurrent Neural Networks (CNNs and RNNs). The book Deep Learning with Python by Francois Chollet, creator of Keras, is a great place to get started. TensorFlow 2. Read chapters 1-4 to understand the fundamentals of ML Jun 12, 2024 · List of the Best TensorFlow Books: Best Tensorflow Books for Beginners. Book description. Now, even programmers who know %PDF-1. O’Reilly members get unlimited access to books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers. ISBN: 978-620-2-07312-7. 0). May 9, 2017 · + Engaging: The book is a joy to read, and the author is quick to respond to issues pointed out by readers in the book or in the Jupyter Notebooks. Apr 24, 2018 · The book also discusses on MDPs, Monte Carlo tree searches, dynamic programming such as policy and value iteration, temporal difference learning such as Q-learning and SARSA. The book emphasizes the unique features of tensorflow 2. This book is for Python developers with a strong interest in deep learning, who want to learn how to leverage TensorFlow to simplify NLP tasks. 4. 0Book Description Following is what you need for this book: TensorFlow Machine Learning Projects is for you if you are a data analyst, data scientist, machine learning professional, or deep learning enthusiast with basic knowledge of TensorFlow. Title: Machine Learning with TensorFlow, Second Edition. docker pull tensorflow/tensorflow:latest # Download latest stable image docker run -it -p 8888:8888 tensorflow/tensorflow:latest-jupyter # Start Jupyter server May 18, 2018 · By Matthew B Richard. Importantnote:Thisprogramisclosingsoon. What you will learnTake TensorFlow into productionImplement and fine-tune Transformer models for various NLP tasksApply reinforcement learning algorithms Dec 20, 2022 · This best-selling book uses concrete examples, minimal theory, and production-ready Python frameworks–scikit-learn, Keras, and TensorFlow–to help you gain an intuitive understanding of the concepts and tools for building intelligent systems. About the Book. By using concrete examples, minimal theory, and two production-ready Python frameworks—scikit-learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. ISBN: 9781800208865. Everything else—Python, TensorFlow 2. Each time you call the model you pass in some text and an internal state. You don't need a supercomputer, you can run the programs in this book from your PC connected to very low cost devices from Arduino, SparkFun and other vendors. Part 1 focuses on the basics of TensorFlow, such as writing a program in TensorFlow, understanding basic data-structures and operations in TensorFlow. You will learn how to use Scikit-Learn, Keras, and TensorFlow to train, fine-tune, and deploy models for various tasks, such as Title: Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, 2nd Edition. Key FeaturesUnderstand the basics of machine learning and discover the power of neural networks and deep learningExplore the structure of the TensorFlow framework and understand how to transition to TF 2. In this chapter, you’ll learn how to define constants and variables, perform tensor addition and multiplication, and compute derivatives. 64. Printed in full color! Unlock the groundbreaking advances of deep learning with this extensively revised new edition of the bestselling original. This is the official code repository for Machine Learning with TensorFlow. Author (s): Aurélien Géron. Publisher (s): O'Reilly Media, Inc. Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. keras API brings Keras’s simplicity and ease of use to the TensorFlow project. By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. This book covers machine learning with a focus on developing neural network-based solutions. 0 and explain how this platform has evolved over the years to become one of the most popular and user-friendly source libraries for machine learning currently available. El Curso intensivo de aprendizaje automático con la API de TensorFlow es una guía de estudio autónomo para quienes aspiran a convertirse en profesionales del aprendizaje automático. Earlier this year, Google announced TensorFlow 2. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. Apprenez les bases du ML à travers une série de livres et de cours en ligne. 2. Jan 21, 2020 · I am using the TinyML book to develop usable, hands-on competence with Tensorflow and machine learning. Implement classical and deep learning generative models through practical examples Key Features Explore creative and human-like capabilities of AI and generate impressive This project aims at teaching you the fundamentals of Machine Learning in python. Starting with TensorFlow 2. In this book, we introduce coding with tensorflow 2. This paper tries to highlight some essential elements that emerge from Luigi Pasinetti's work. CandidateHandbook. ISBN: 9781492090793. The third edition of the highly regarded, best-selling Python machine learning book. ISBN: 9781491978740. This book will help you explore TensorFlow 2, the brand new version of Google's open source framework for machine learning. "Unlock the full potential of TensorFlow with 'Mastering Deep Learning with TensorFlow: Advanced Methods and Practical Implementations in Neural Networks, Computer Vision, NLP, and Transformers. System requirements. Given the demand for AI and the ubiquity of JavaScript, TensorFlow. Author (s): Gant Laborde. This Lesson will answer your key questions about getting started with TensorFlow, a library for machine learning and working with deep neural networks. Release date: January 2021. Knowledge of linear algebra will be helpful, but not necessary. Released. about the book TensorFlow in Action teaches you to construct, train, and deploy deep learning models using TensorFlow 2. This book starts with ensemble methods and their features. '. Release date: October 2022. The simplest way to generate text with this model is to run it in a loop, and keep track of the model's internal state as you execute it. Read this book using Google Play Books app on your PC, android, iOS devices. Revised and expanded for TensorFlow 2, GANs, and reinforcement learning. December 2017. Aug 2, 2022 · Predictive modeling with deep learning is a skill that modern developers need to know. Much of the research project that Pasinetti developed, especially in the 1981 book, was already present in nuce in the 1974 collection of essays. Release date: April 2017. Author (s): Amita Kapoor, Antonio Gulli, Sujit Pal. TensorFlow in Action teaches you to construct, train, and deploy deep learning models using TensorFlow 2. Author (s): Tom Hope, Yehezkel S. Write modern natural language processing applications using deep learning algorithms and TensorFlow. This is covered in two main parts, with subsections: Forecast for a single time step: A single feature. Release date: February 2021. 99. Fundamental Python skills are assumed, as well as some knowledge of machine 5 Free Books to Learn Statistics For Data Science – Data Science Tutorials. With this Google framework, seasoned AI veterans and web developers alike can help propel the future of …. The book emphasises on hands-on and practical See full list on github. Publisher: LAP LAMBERT Academic Publishing. Title: Getting started with TensorFlow. The 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. 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 Mar 30, 2018 · Book Description Deep learning is a branch of machine learning algorithms based on learning multiple levels of abstraction. Sep 25, 2023 · Course. 0 uses an API called Keras. by Antonio Gulli, Amita Kapoor, Sujit Pal. js. We show how to develop with tensorflow 1. Upon completing this book, you’ll have the knowledge and skills to build your own computer vision applications using neural networks . the fact that they're the same data sets used elsewhere didn't make them Sep 5, 2019 · This practical book shows you how. ISBN: 9781492032649. TFX provides software frameworks and tooling for full Step 1: Understand what ML is all about. Dec 24, 2020 · The Hands-On Image Generation with TensorFlow book is for deep learning engineers, practitioners, and researchers who have basic knowledge of convolutional neural networks and want to learn various image generation techniques using TensorFlow 2. You will be introduced to common deep networks such as, fully connected networks, convolution neural networks and recurrent neural networks and Transformers. TensorFlow Certificate: Candidate Handbook. Next, you will learn about convolutional neural networks subscription. Evaluate the accuracy of the model. This short introduction uses Keras to: Load a prebuilt dataset. 81. js was inevitable. ISBN: None. About the Technology. x. Train this neural network. 2) Advanced Deep Learning with TensorFlow 2 and Keras. Deep Learning with TensorFlow 2 and Keras, 2nd Edition. This book is also for you if you want to build end-to-end projects in the machine learning domain using supervised Hands-On Convolutional Neural Networks with TensorFlow. In Deep Learning with Python, Second 4) Mastering TensorFlow 1. Jan 23, 2021 · This practical book provides an end-to-end guide to TensorFlow, the leading open source software library that helps you build and train neural networks for deep learning, Natural Language Processing (NLP), speech recognition, and general predictive analytics. Download for offline reading, highlight, bookmark or take notes while you read Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Edition 3. Dec 12, 2019 · Applied machine learning with a solid foundation in theory. Gain an intuitive understanding of neural networks without the dense jargon. Release date: August 2017. ISBN: 9781803232911. Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2. 99 $37. ISBN: 9781788835725. It contains the example code and solutions to the exercises in the third edition of my O'Reilly book Hands-on Machine Learning with Scikit-Learn, Keras and TensorFlow (3rd edition): Note: If you are looking for the second edition notebooks, check out ageron Nishant Shukla | 4. Build cutting edge machine and deep learning systems for the lab, production, and mobile devices. What You Will Learn Mar 23, 2024 · Download notebook. Machine Learning is great for: Problems for which existing solutions require a lot of fine-tuning or long lists of rules: one Machine Learning algorithm can often simplify code and perform better than the traditional approach. x to 2. ISBN: 9781789130331. Sep 13, 2019 · With TensorFlow (TF) 2. Resheff (Ebook): This book provides an end-to-end guide to TensorFlow, helping you to train and build neural networks for computer vision, NLP, speech recognition, general predictive analytics and others. 3) Tensorflow in 1 Day. 99 | Publisher: Packt Publishing | Release: 2022. This book builds upon the foundations established in its first edition, with updated chapters and the latest code implementations to bring it up to date with Tensorflow 2. This is my first book, and a very special one indeed. at 800-232-0223(toll free). This book covers the end-to-end ML process using Microsoft Azure Machine Learning, including data preparation, performing and logg Price: $41. 6 %âãÏÓ 2 0 obj /Type /Catalog /Names 4 0 R /Pages 5 0 R /AcroForm 6 0 R /MarkInfo /Marked true >> /Metadata 7 0 R /Outlines 8 0 R /PageLabels 9 0 R /StructTreeRoot 10 0 R /ViewerPreferences /Direction /L2R >> >> endobj 7 0 obj /Type /Metadata /Length 4480 /Subtype /XML >> stream 2017-02-13T18:23:14+04:00 2017-02-13T19:56:33+05:30 2017-05-19T16:21:25+04:00 Adobe InDesign CS6 Hands-On Machine Learning with Scikit-Learn and TensorFlow. The course also introduces transfer learning, leveraging pre-trained models for enhanced performance. Build a neural network machine learning model that classifies images. Key Features:-. Authors: Ahmed Fawzy Gad The book’s source code has been updated from TensorFlow 1. x and the Google Colab cloud service. The model returns a prediction for the next character and its new state. Title: Generative AI with Python and TensorFlow 2. What you’ll learn—and how you can Title: Learning TensorFlow. Cons: - Experts may find this book lacks enough depth because it is more focused on getting up and running rather than Dec 24, 2019 · Part I, The Fundamentals of Machine Learning. In this practical tutorial, you’ll build reusable skill hands-on as you create production-ready applications such as a French-to-English translator and a neural network that can write fiction. First, this book did a great job of explaining how tensorflow can be used to solve different types of problems, such as computer vision, natural language processing, and time series forecasting. Deep learning is quickly integrating itself into the technology landscape. TensorFlow is a free and open-source software library for machine learning. Les bases du machine learning avec TensorFlow. Hands-On Neural Networks with TensorFlow 2. 16 | Mar 14, 2024 | 213 Pages. 10 was the last TensorFlow release that supported GPU on native-Windows. ISBN: 9781491978511. and accurate predictive models with the power of TensorFlow v1. Release date: May 2021. This tutorial is an introduction to time series forecasting using TensorFlow. 0 is designed to make building neural networks for machine learning easy, which is why TensorFlow 2. Author (s): Alexia Audevart, Konrad Banachewicz, Luca Massaron. 0. Title: Learning TensorFlow. ISBN: 9781800200883. Feb 12, 2018 · Machine Learning with TensorFlow. Stefano Lucarelli. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow is a comprehensive guide that covers concepts, tools, and techniques to build intelligent systems. Chapter 4: How to debug a memory leak in TensorFlow. Clearly, the author enjoys machine learning and teaching it to others. Pro Deep Learning with TensorFlow 2. keras allows you to design, […] Mar 13, 2017 · This practical book shows you how. Chapter 2: Creating a custom operation with tf. - free book at FreeComputerBooks. Master TensorFlow to create powerful machine learning algorithms, with valuable insights on Keras, Boosted Trees, Tabular Data, Transformers Mar 24, 2023 · The TensorFlow Docker images are already configured to run TensorFlow. This tutorial is a Google Colaboratory notebook. L a st Upd a t e d : Fe b 5, 2024. 0, it is a major leap from the existing Title: Deep Learning with TensorFlow and Keras - Third Edition. Key FeaturesExplore the most advanced deep learning techniques that drive modern AI resultsNew coverage of unsupervised deep learning using mutual information, object detection, and semantic segmentationCompletely updated for TensorFlow 2. You'll begin by reviewing the Markov decision processes This project aims at teaching you the fundamentals of Machine Learning in python. Everyday low prices and free delivery on eligible orders. You will see that scikit-learn provides Jan 12, 2024 · Book LInk. The book is a great starting point for learning this technology. Incluye una serie de lecciones con clases por video, casos de éxito reales y ejercicios prácticos. . Publisher (s): Manning Publications. As mentioned by Pramod, the objective of this book is to introduce readers to TensorFlow 2. Chapter 1: Getting started with tensorflow. Released August 2018. 7 Nov 16, 2023 · TensorFlow 2 quickstart for beginners. Mastering Predictive Analytics with scikit-learn and TensorFlow covers various implementations of ensemble methods, how they are used with real-world datasets, and how they improve prediction accuracy in classification and regression problems. Read it now on the O’Reilly learning platform with a 10-day free trial. Theano Theano is another deep-learning library with python-wrapper (was inspiration for Tensorflow) Theano and TensorFlow are very similar systems. It even went into text generation, which got my creativity going. com Aurélien Géron Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow Concepts, Tools, and Techniques to Build Intelligent Systems SECOND EDITION Learning tensorflow eBook (PDF) Download this eBook for free. Our Free TensorFlow Course, designed for beginners to master Neural Networks, Image Classification, and more in just 3 hours. Dive into the cutting-edge techniques and methodologies that empower you to push the This practical book shows you how. Key FeaturesThird edition of the bestselling, widely acclaimed Python machine learning bookClear and intuitive explanations take you deep into the theory and practice of Python machine Oct 1, 2020 · I enjoyed this book from cover to cover, and I am especially thankful for a few things. Written by the main authors of the TensorFlow library, this new book provides fascinating use cases and in-depth instruction for deep learning apps in JavaScript in your browser or on Node. Although using TensorFlow directly can be challenging, the modern tf. from $19. Explore the structure of the TensorFlow framework and understand how to transition to TF 2. 0: Implement Machine Learning and Deep Learning Models with Python. Jul 20, 2018 · Claim your free book here. #3 Best Choice. For additional information, please contact the Customer Service Dept. TensorFlowDeveloperCerticate. ig oy sp zg ov er qn sa ty wn