You're reading from Azure Data Scientist Associate Certification Guide

Product typeBook

Published inDec 2021

Reading LevelBeginner

PublisherPackt

ISBN-139781800565005

Edition1st Edition

Languages

Python

Tools

Azure Functions

Concepts

Machine Learning

Authors (2):

Andreas Botsikas

Michael Hlobil

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Who this book is for

The book targets two audiences: developers who seek to infuse their applications with AI capabilities and data scientists who want to scale their ML experiments in the Azure cloud. Basic knowledge of Python is needed to follow the code samples present in the book. Some experience in training ML models in Python with common frameworks such as scikit-learn will help you understand the content more easily.

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Azure Data Scientist Associate Certification Guide

Published in: Dec 2021Publisher: PacktISBN-13: 9781800565005

Authors (2)

Andreas Botsikas

Andreas Botsikas is an experienced advisor working in the software industry. He has worked in the finance sector, leading highly efficient DevOps teams, and architecting and building high-volume transactional systems. He then traveled the world, building AI-infused solutions with a group of engineers and data scientists. Currently, he works as a trusted advisor for customers onboarding into Azure, de-risking and accelerating their cloud journey. He is a strong engineering professional with a Doctor of Philosophy (Ph.D.) in resource optimization with artificial intelligence from the National Technical University of Athens.
Read more about Andreas Botsikas

Michael Hlobil

Michael Hlobil is an experienced architect focused on quickly understanding customers' business needs, with over 25 years of experience in IT pitfalls and successful projects, and is dedicated to creating solutions based on the Microsoft Platform. He has an MBA in Computer Science and Economics (from the Technical University and the University of Vienna) and an MSc (from the ESBA) in Systemic Coaching. He was working on advanced analytics projects in the last decade, including massive parallel systems and Machine Learning systems. He enjoys working with customers and supporting the journey to the cloud.
Read more about Michael Hlobil

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