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Azure Data Scientist Associate Certification Guide

You're reading from Azure Data Scientist Associate Certification Guide A hands-on guide to machine learning in Azure and passing the Microsoft Certified DP-100 exam

Product type Paperback

Published in Dec 2021

Publisher Packt

ISBN-13 9781800565005

Length 448 pages

Edition 1st Edition

Languages

Python

Tools

Azure

Concepts

Machine Learning

Authors (2):

Andreas Botsikas

Michael Hlobil

View More author details

Table of Contents (17) Chapters

Preface

1. Section 1: Starting your cloud-based data science journey

2. Chapter 1: An Overview of Modern Data Science FREE CHAPTER

3. Chapter 2: Deploying Azure Machine Learning Workspace Resources

4. Chapter 3: Azure Machine Learning Studio Components

5. Chapter 4: Configuring the Workspace

6. Section 2: No code data science experimentation

7. Chapter 5: Letting the Machines Do the Model Training

8. Chapter 6: Visual Model Training and Publishing

9. Section 3: Advanced data science tooling and capabilities

10. Chapter 7: The AzureML Python SDK

11. Chapter 8: Experimenting with Python Code

12. Chapter 9: Optimizing the ML Model

13. Chapter 10: Understanding Model Results

14. Chapter 11: Working with Pipelines

15. Chapter 12: Operationalizing Models with Code

16. Other Books You May Enjoy

Questions

In each chapter, you will find a couple of questions to help you conduct a knowledge check regarding the topics that have been discussed in each chapter:

You are using TabularExplainer to interpret a sklearn DecisionTreeClassifier. Which underlying SHAP explainer will be used?
a. DecisionTreeExplainer
b. TreeExplainer
c. KernelExplainer
d. LinearExplainer
You want to interpret a sklearn DecisionTreeClassifier using MimicExplainer. Which of the following models can you use for the explainable_model parameter?
a. LGBMExplainableModel
b. LinearExplainableModel
c. SGDExplainableModel
d. DecisionTreeExplainableModel
e. All of the above
Can you use PFIExplainer to produce local feature importance values?
a. Yes
b. No

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Authors (2)

Andreas Botsikas

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.

See other products by Andreas Botsikas

Hlobil

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.

See other products by Hlobil

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