Tensorflow machine learning tutorial par flores dwayne (4 résultats)

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  • Langue : anglais

    Edité par Amazon Digital Services LLC - Kdp, 2025

    9798287212896

    Série : Livre 4 sur 5 - Machine Learning Mastery Toolkit

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    Vendeur : PBShop.store US, Wood Dale, IL, Etats-UnisPBShop.store US

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    EUR 32,79

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    PAP. Etat : New. New Book. Shipped from UK. Established seller since 2000.

  • Langue : anglais

    Edité par Amazon Digital Services LLC - Kdp, 2025

    9798287212896

    Série : Livre 4 sur 5 - Machine Learning Mastery Toolkit

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    Vendeur : PBShop.store UK, Fairford, GLOS, Royaume-UniPBShop.store UK

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    EUR 28,75

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    PAP. Etat : New. New Book. Shipped from UK. Established seller since 2000.

  • Langue : anglais

    Edité par Independently Published, 2025

    9798287212896

    Série : Livre 4 sur 5 - Machine Learning Mastery Toolkit

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    Vendeur : Grand Eagle Retail, Bensenville, IL, Etats-UnisGrand Eagle Retail

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    EUR 32,78

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    Paperback. Etat : new. Paperback. Are you ready to conquer the complexities of TensorFlow and deliver realworld machine learning systems that scale? Many developers struggle to move beyond proof-of-concepts-models that work on a laptop but buckle under production demands.TensorFlow Machine Learning Tutorial for Developers provides the step-by-step playbook you need to build, optimize, and deploy production-ready models with confidence. From crafting high-throughput data pipelines and writing custom training loops with tf.GradientTape to applying mixed-precision, pruning, and quantization, this book transforms theory into practice. You'll master end-to-end workflows-containerized training on GPUs, serving with TensorFlow Serving or FastAPI, autoscaling in Kubernetes, serverless inference on Cloud Functions, and continuous retraining with TFX.What you'll achieve: Efficient Data Engineering: Implement tf.data pipelines that load, augment, and shard data for multi-GPU/TPU training.Advanced Model Development: Build models using tf.keras Sequential and Functional APIs, custom layers, attention blocks, and transfer learning modules.Performance Tuning: Apply mixed-precision training, XLA compilation, and distribution strategies to accelerate throughput.Edge and Cloud Deployment: Package models in Docker, deploy on Kubernetes with autoscaling, or host serverless TFLite microservices on AWS Lambda and Cloud Run.Robust MLOps Practices: Set up monitoring with Prometheus, Grafana, TensorBoard, detect data drift with TFDV, and automate CI/CD via GitHub Actions.Are you curious how to scale a Transformer-based chatbot, run inference on a microcontroller, or automate a TFX pipeline that retrains itself? This hands-on guide delivers complete, ready-to-run code examples-no fluff, no theory overload.Take the next step to transform your machine learning skills into production excellence. Grab your copy of TensorFlow Machine Learning Tutorial for Developers today and start building models that perform, scale, and endure. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

  • Langue : anglais

    Edité par Independently Published, 2025

    9798287212896

    Série : Livre 4 sur 5 - Machine Learning Mastery Toolkit

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    Vendeur : CitiRetail, Stevenage, Royaume-UniCitiRetail

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    Etat: Neuf

    EUR 32,77

    EUR 43,62 expédition 
    Expédition depuis Royaume-Uni vers Etats-Unis

    Quantité disponible : 1 disponible

    Paperback. Etat : new. Paperback. Are you ready to conquer the complexities of TensorFlow and deliver realworld machine learning systems that scale? Many developers struggle to move beyond proof-of-concepts-models that work on a laptop but buckle under production demands.TensorFlow Machine Learning Tutorial for Developers provides the step-by-step playbook you need to build, optimize, and deploy production-ready models with confidence. From crafting high-throughput data pipelines and writing custom training loops with tf.GradientTape to applying mixed-precision, pruning, and quantization, this book transforms theory into practice. You'll master end-to-end workflows-containerized training on GPUs, serving with TensorFlow Serving or FastAPI, autoscaling in Kubernetes, serverless inference on Cloud Functions, and continuous retraining with TFX.What you'll achieve: Efficient Data Engineering: Implement tf.data pipelines that load, augment, and shard data for multi-GPU/TPU training.Advanced Model Development: Build models using tf.keras Sequential and Functional APIs, custom layers, attention blocks, and transfer learning modules.Performance Tuning: Apply mixed-precision training, XLA compilation, and distribution strategies to accelerate throughput.Edge and Cloud Deployment: Package models in Docker, deploy on Kubernetes with autoscaling, or host serverless TFLite microservices on AWS Lambda and Cloud Run.Robust MLOps Practices: Set up monitoring with Prometheus, Grafana, TensorBoard, detect data drift with TFDV, and automate CI/CD via GitHub Actions.Are you curious how to scale a Transformer-based chatbot, run inference on a microcontroller, or automate a TFX pipeline that retrains itself? This hands-on guide delivers complete, ready-to-run code examples-no fluff, no theory overload.Take the next step to transform your machine learning skills into production excellence. Grab your copy of TensorFlow Machine Learning Tutorial for Developers today and start building models that perform, scale, and endure. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…