Tensorflow 2 (228 Ergebnisse)

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Paperback. Zustand: Very Good. This third edition is updated with TensorFlow 2 and the latest additions to scikit-learn. Packed with clear explanations, visualizations, and working examples, the book covers essential machine learning techniques in depth, along with two cutting-edge machine learning techniques: reinforcement learning and generative adversarial networks.…

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Paperback. Zustand: Very Good. Packed with intriguing real-world projects as well as theory, Generative AI with Python and TensorFlow 2 enables you to leverage artificial intelligence creatively and generate human-like data in the form of speech, text, images, and music.

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Paperback. Zustand: Good. This third edition is updated with TensorFlow 2 and the latest additions to scikit-learn. Packed with clear explanations, visualizations, and working examples, the book covers essential machine learning techniques in depth, along with two cutting-edge machine learning techniques: reinforcement learning and generative adversarial networks.…

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Paperback. Zustand: Very Good. 2nd ed. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

Sprache: Englisch
Verlag: Packt Publishing, 2019
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Paperback. Zustand: New. This easy-to-use reference for TensorFlow 2 design patterns in Python will help you make informed decisions for various use cases. Author KC Tung addresses common topics and tasks in enterprise data science and machine learning practices rather than focusing on TensorFlow itself.When and why would you feed training data as using NumPy or a streaming dataset? How would you set up cross-validations in the training process? How do you leverage a pretrained model using transfer learning? How do you perform hyperparameter tuning? Pick up this pocket reference and reduce the time you spend searching through options for your TensorFlow use cases.Understand best practices in TensorFlow model patterns and ML workflowsUse code snippets as templates in building TensorFlow models and workflowsSave development time by integrating prebuilt models in TensorFlow HubMake informed design choices about data ingestion, training paradigms, model saving, and inferencingAddress common scenarios such as model design style, data ingestion workflow, model training, and tuning.…

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Paperback. Zustand: Fair. 3rd ed. The item might be beaten up but readable. May contain markings or highlighting, as well as stains, bent corners, or any other major defect, but the text is not obscured in any way.

Sprache: Englisch
Verlag: Packt Publishing, 2019
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Paperback. Zustand: Very Good. Deep Learning with TensorFlow 2 and Keras This book is in very good condition and will be shipped within 24 hours of ordering. The cover may have some limited signs of wear but the pages are clean, intact and the spine remains undamaged. This book has clearly been well maintained and looked after thus far. Money back guarantee if you are not satisfied. See all our books here, order more than 1 book and get discounted shipping. .…

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- Softcover
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Paperback. Zustand: Good. Work through practical recipes to learn how to solve complex machine learning and deep learning problems using Python Key Features Get up and running with artificial intelligence in no time using hands-on problem-solving recipes Explore popular Python libraries and tools to build AI solutions for images, text, sounds, and images Implement NLP, reinforcement learning, deep learning, GANs, Monte-Carlo tree search, and much more Book DescriptionArtificial intelligence (AI) plays an integral role in automating problem-solving. This involves predicting and classifying data and training agents to execute tasks successfully. This book will teach you how to solve complex problems with the help of independent and insightful recipes ranging from the essentials to advanced methods that have just come out of research. Artificial Intelligence with Python Cookbook starts by showing you how to set up your Python environment and taking you through the fundamentals of data exploration. Moving ahead, you?ll be able to implement heuristic search techniques and genetic algorithms. In addition to this, you'll apply probabilistic models, constraint optimization, and reinforcement learning. As you advance through the book, you'll build deep learning models for text, images, video, and audio, and then delve into algorithmic bias, style transfer, music generation, and AI use cases in the healthcare and insurance industries. Throughout the book, you?ll learn about a variety of tools for problem-solving and gain the knowledge needed to effectively approach complex problems. By the end of this book on AI, you will have the skills you need to write AI and machine learning algorithms, test them, and deploy them for production.What you will learn Implement data preprocessing steps and optimize model hyperparameters Delve into representational learning with adversarial autoencoders Use active learning, recommenders, knowledge embedding, and SAT solvers Get to grips with probabilistic modeling with TensorFlow probability Run object detection, text-to-speech conversion, and text and music generation Apply swarm algorithms, multi-agent systems, and graph networks Go from proof of concept to production by deploying models as microservices Understand how to use modern AI in practice Who this book is forThis AI machine learning book is for Python developers, data scientists, machine learning engineers, and deep learning practitioners who want to learn how to build artificial intelligence solutions with easy-to-follow recipes. You?ll also find this book useful if you?re looking for state-of-the-art solutions to perform different machine learning tasks in various use cases. Basic working knowledge of the Python programming language and machine learning concepts will help you to work with code effectively in this book.…

- Softcover
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Paperback. Zustand: New. This easy-to-use reference for TensorFlow 2 design patterns in Python will help you make informed decisions for various use cases. Author KC Tung addresses common topics and tasks in enterprise data science and machine learning practices rather than focusing on TensorFlow itself.When and why would you feed training data as using NumPy or a streaming dataset? How would you set up cross-validations in the training process? How do you leverage a pretrained model using transfer learning? How do you perform hyperparameter tuning? Pick up this pocket reference and reduce the time you spend searching through options for your TensorFlow use cases.Understand best practices in TensorFlow model patterns and ML workflowsUse code snippets as templates in building TensorFlow models and workflowsSave development time by integrating prebuilt models in TensorFlow HubMake informed design choices about data ingestion, training paradigms, model saving, and inferencingAddress common scenarios such as model design style, data ingestion workflow, model training, and tuning.…

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- Softcover
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Paperback. Zustand: Good. A comprehensive guide to get you up to speed with the latest developments of practical machine learning with Python and upgrade your understanding of machine learning (ML) algorithms and techniques Key Features Dive into machine learning algorithms to solve the complex challenges faced by data scientists today Explore cutting edge content reflecting deep learning and reinforcement learning developments Use updated Python libraries such as TensorFlow, PyTorch, and scikit-learn to track machine learning projects end-to-end Book DescriptionPython Machine Learning By Example, Third Edition serves as a comprehensive gateway into the world of machine learning (ML). With six new chapters, on topics including movie recommendation engine development with Naïve Bayes, recognizing faces with support vector machine, predicting stock prices with artificial neural networks, categorizing images of clothing with convolutional neural networks, predicting with sequences using recurring neural networks, and leveraging reinforcement learning for making decisions, the book has been considerably updated for the latest enterprise requirements. At the same time, this book provides actionable insights on the key fundamentals of ML with Python programming. Hayden applies his expertise to demonstrate implementations of algorithms in Python, both from scratch and with libraries. Each chapter walks through an industry-adopted application. With the help of realistic examples, you will gain an understanding of the mechanics of ML techniques in areas such as exploratory data analysis, feature engineering, classification, regression, clustering, and NLP. By the end of this ML Python book, you will have gained a broad picture of the ML ecosystem and will be well-versed in the best practices of applying ML techniques to solve problems.What you will learn Understand the important concepts in ML and data science Use Python to explore the world of data mining and analytics Scale up model training using varied data complexities with Apache Spark Delve deep into text analysis and NLP using Python libraries such NLTK and Gensim Select and build an ML model and evaluate and optimize its performance Implement ML algorithms from scratch in Python, TensorFlow 2, PyTorch, and scikit-learn Who this book is forIf you?re a machine learning enthusiast, data analyst, or data engineer highly passionate about machine learning and want to begin working on machine learning assignments, this book is for you. Prior knowledge of Python coding is assumed and basic familiarity with statistical concepts will be beneficial, although this is not necessary.…

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- Softcover
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Zustand: New. Brand New. Soft Cover International Edition. Different ISBN and Cover Image. Priced lower than the standard editions which is usually intended to make them more affordable for students abroad. The core content of the book is generally the same as the standard edition. The country selling restrictions may be printed on the book but is no problem for the self-use. This Item maybe shipped from US or any other country as we have multiple locations worldwide.…