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The Deep Learning Architect's Handbook. Build and deploy production-ready DL solutions leveraging the latest Python techniques

(ebook) (audiobook) (audiobook) Książka w języku 1
Autor:
Ee Kin Chin
The Deep Learning Architect's Handbook. Build and deploy production-ready DL solutions leveraging the latest Python techniques Ee Kin Chin - okladka książki

The Deep Learning Architect's Handbook. Build and deploy production-ready DL solutions leveraging the latest Python techniques Ee Kin Chin - okladka książki

The Deep Learning Architect's Handbook. Build and deploy production-ready DL solutions leveraging the latest Python techniques Ee Kin Chin - audiobook MP3

The Deep Learning Architect's Handbook. Build and deploy production-ready DL solutions leveraging the latest Python techniques Ee Kin Chin - audiobook CD

Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
516
Dostępne formaty:
     PDF
     ePub
Deep learning enables previously unattainable feats in automation, but extracting real-world business value from it is a daunting task. This book will teach you how to build complex deep learning models and gain intuition for structuring your data to accomplish your deep learning objectives.
This deep learning book explores every aspect of the deep learning life cycle, from planning and data preparation to model deployment and governance, using real-world scenarios that will take you through creating, deploying, and managing advanced solutions. You’ll also learn how to work with image, audio, text, and video data using deep learning architectures, as well as optimize and evaluate your deep learning models objectively to address issues such as bias, fairness, adversarial attacks, and model transparency.
As you progress, you’ll harness the power of AI platforms to streamline the deep learning life cycle and leverage Python libraries and frameworks such as PyTorch, ONNX, Catalyst, MLFlow, Captum, Nvidia Triton, Prometheus, and Grafana to execute efficient deep learning architectures, optimize model performance, and streamline the deployment processes. You’ll also discover the transformative potential of large language models (LLMs) for a wide array of applications.
By the end of this book, you'll have mastered deep learning techniques to unlock its full potential for your endeavors.

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O autorze książki

Ee Kin Chin is a Senior Deep Learning Engineer at DataRobot. He holds a Bachelor of Engineering (Honours) in Electronics with a major in Telecommunications. Ee Kin is an expert in the field of Deep Learning, Data Science, Machine Learning, Artificial Intelligence, Supervised Learning, Unsupervised Learning, Python, Keras, Pytorch, and related technologies. He has a proven track record of delivering successful projects in these areas and is dedicated to staying up to date with the latest advancements in the field.

Packt Publishing - inne książki

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