Building Scalable Deep Learning Pipelines on AWS

Develop, Train, and Deploy Deep Learning Models

Éditeur :

Apress

Paru le : 2024-12-19

This book is your comprehensive guide to creating powerful, end-to-end deep learning workflows on Amazon Web Services (AWS). The book explores how to integrate essential big data tools and technologies—such as PySpark, PyTorch, TensorFlow, Airflow, EC2, and S3—to streamline the development, tra...
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Éditeur

Collection
n.c

Parution
2024-12-19

Pages
760 pages

EAN papier
9798868810169

Auteur(s) du livre


Abdelaziz Testas, PhD, is a seasoned data scientist with over a decade of experience in data analysis and machine learning. He earned his PhD in Economics from the University of Leeds in England and holds a master’s degree in the same field from the University of Glasgow in Scotland. Additionally, he has earned several certifications in computer science and data science in the United States. For over 10 years, Abdelaziz served as a Lead Data Scientist at Nielsen, where he played a pivotal role in enhancing the company’s audience measurement capabilities. He was instrumental in planning, initiating, and executing end-to-end data science projects and developing methodologies that advanced Nielsen’s digital ad and content rating products. His expertise in media measurement and data science drove the creation of innovative solutions. Recently, Abdelaziz transitioned to the public sector, joining the State of California's Department of Health Care Access and Information (HCAI). In his new role, he leverages his coding and data science leadership skills to make a meaningful impact, supporting HCAI’s mission to ensure quality, equitable, and affordable health care for all Californians. Abdelaziz is also the author of Distributed Machine Learning with PySpark: Migrating Effortlessly from Pandas and Scikit-Learn (Apress).

Caractéristiques détaillées - droits

EAN PDF
9798868810176
Prix
54,22 €
Nombre pages copiables
7
Nombre pages imprimables
76
Taille du fichier
5898 Ko
EAN EPUB
9798868810176
Prix
54,22 €
Nombre pages copiables
7
Nombre pages imprimables
76
Taille du fichier
1505 Ko

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