Buy TensorFlow Machine Learning Tutorial for Developers
Book 1
Book 2
Book 3
Book 1
Book 2
Book 3
Book 1
Book 2
Book 3
Book 1
Book 2
Book 3
Home > Computing and Information Technology > Computer science > Artificial intelligence > TensorFlow Machine Learning Tutorial for Developers: Build, Optimize, and Deploy Production-Ready Models(Machine Learning Mastery Toolkit)
TensorFlow Machine Learning Tutorial for Developers: Build, Optimize, and Deploy Production-Ready Models(Machine Learning Mastery Toolkit)

TensorFlow Machine Learning Tutorial for Developers: Build, Optimize, and Deploy Production-Ready Models(Machine Learning Mastery Toolkit)


     0     
5
4
3
2
1



International Edition


X
About the Book

Are you ready to conquer the complexities of TensorFlow and deliver real‐world 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.


Best Sellers


Product Details
  • ISBN-13: 9798287212896
  • Publisher: Independently Published
  • Publisher Imprint: Independently Published
  • Height: 254 mm
  • No of Pages: 364
  • Returnable: N
  • Spine Width: 19 mm
  • Weight: 680 gr
  • ISBN-10: 8287212898
  • Publisher Date: 07 Jun 2025
  • Binding: Paperback
  • Language: English
  • Returnable: N
  • Series Title: Machine Learning Mastery Toolkit
  • Sub Title: Build, Optimize, and Deploy Production-Ready Models
  • Width: 178 mm


Similar Products

Add Photo
Add Photo

Customer Reviews

REVIEWS      0     
Click Here To Be The First to Review this Product
TensorFlow Machine Learning Tutorial for Developers: Build, Optimize, and Deploy Production-Ready Models(Machine Learning Mastery Toolkit)
Independently Published -
TensorFlow Machine Learning Tutorial for Developers: Build, Optimize, and Deploy Production-Ready Models(Machine Learning Mastery Toolkit)
Writing guidlines
We want to publish your review, so please:
  • keep your review on the product. Review's that defame author's character will be rejected.
  • Keep your review focused on the product.
  • Avoid writing about customer service. contact us instead if you have issue requiring immediate attention.
  • Refrain from mentioning competitors or the specific price you paid for the product.
  • Do not include any personally identifiable information, such as full names.

TensorFlow Machine Learning Tutorial for Developers: Build, Optimize, and Deploy Production-Ready Models(Machine Learning Mastery Toolkit)

Required fields are marked with *

Review Title*
Review
    Add Photo Add up to 6 photos
    Would you recommend this product to a friend?
    Tag this Book Read more
    Does your review contain spoilers?
    What type of reader best describes you?
    I agree to the terms & conditions
    You may receive emails regarding this submission. Any emails will include the ability to opt-out of future communications.

    CUSTOMER RATINGS AND REVIEWS AND QUESTIONS AND ANSWERS TERMS OF USE

    These Terms of Use govern your conduct associated with the Customer Ratings and Reviews and/or Questions and Answers service offered by Bookswagon (the "CRR Service").


    By submitting any content to Bookswagon, you guarantee that:
    • You are the sole author and owner of the intellectual property rights in the content;
    • All "moral rights" that you may have in such content have been voluntarily waived by you;
    • All content that you post is accurate;
    • You are at least 13 years old;
    • Use of the content you supply does not violate these Terms of Use and will not cause injury to any person or entity.
    You further agree that you may not submit any content:
    • That is known by you to be false, inaccurate or misleading;
    • That infringes any third party's copyright, patent, trademark, trade secret or other proprietary rights or rights of publicity or privacy;
    • That violates any law, statute, ordinance or regulation (including, but not limited to, those governing, consumer protection, unfair competition, anti-discrimination or false advertising);
    • That is, or may reasonably be considered to be, defamatory, libelous, hateful, racially or religiously biased or offensive, unlawfully threatening or unlawfully harassing to any individual, partnership or corporation;
    • For which you were compensated or granted any consideration by any unapproved third party;
    • That includes any information that references other websites, addresses, email addresses, contact information or phone numbers;
    • That contains any computer viruses, worms or other potentially damaging computer programs or files.
    You agree to indemnify and hold Bookswagon (and its officers, directors, agents, subsidiaries, joint ventures, employees and third-party service providers, including but not limited to Bazaarvoice, Inc.), harmless from all claims, demands, and damages (actual and consequential) of every kind and nature, known and unknown including reasonable attorneys' fees, arising out of a breach of your representations and warranties set forth above, or your violation of any law or the rights of a third party.


    For any content that you submit, you grant Bookswagon a perpetual, irrevocable, royalty-free, transferable right and license to use, copy, modify, delete in its entirety, adapt, publish, translate, create derivative works from and/or sell, transfer, and/or distribute such content and/or incorporate such content into any form, medium or technology throughout the world without compensation to you. Additionally,  Bookswagon may transfer or share any personal information that you submit with its third-party service providers, including but not limited to Bazaarvoice, Inc. in accordance with  Privacy Policy


    All content that you submit may be used at Bookswagon's sole discretion. Bookswagon reserves the right to change, condense, withhold publication, remove or delete any content on Bookswagon's website that Bookswagon deems, in its sole discretion, to violate the content guidelines or any other provision of these Terms of Use.  Bookswagon does not guarantee that you will have any recourse through Bookswagon to edit or delete any content you have submitted. Ratings and written comments are generally posted within two to four business days. However, Bookswagon reserves the right to remove or to refuse to post any submission to the extent authorized by law. You acknowledge that you, not Bookswagon, are responsible for the contents of your submission. None of the content that you submit shall be subject to any obligation of confidence on the part of Bookswagon, its agents, subsidiaries, affiliates, partners or third party service providers (including but not limited to Bazaarvoice, Inc.)and their respective directors, officers and employees.

    Accept

    Fresh on the Shelf


    Inspired by your browsing history


    Your review has been submitted!

    You've already reviewed this product!