Description
Chapter 1 Data Science in the modern enterprise
What is Data Science
The Data Scientists' tools and lingo
Ethics and ethical AI
Significance of Data Science in organizations
Case Studies of applied Data Science
Chapter 2 Most important Statistical Tehniques in Data Science
Top Statistical Tehniques Data Scientists need to know
Supervised Learning
Unsupervised Learning
Regression/Classification/ Forecasting
Bayesian method
Time series analysis
Linear regression
Sampling methods
Reinforcement Learning
Part 2 - Machine Learning in Microsoft Azure &n
Author: Julian Soh, Priyanshi Singh
Publisher: Apress
Published: 01/01/2021
Pages: 285
Binding Type: Paperback
Weight: 0.93lbs
Size: 9.21h x 6.14w x 0.63d
ISBN13: 9781484264041
ISBN10: 1484264045
BISAC Categories:
- Computers | Programming | Microsoft
About the Author
Julian Soh is a cloud solutions architect with Microsoft, focusing in the areas of artificial intelligence, cognitive services, and advanced analytics. Prior to his current role, Julian worked extensively in major public cloud initiatives, such as SaaS (Microsoft Office 365), IaaS/PaaS (Microsoft Azure), and hybrid private-public cloud implementations.
Priyanshi Singh is a data scientist by training and a data enthusiast by nature specializing in machine learning techniques applied to predictive analytics, computer vision and natural language processing. She holds a master's degree in Data Science from New York University and is currently a Cloud Solution Architect at Microsoft helping the public sector to transform citizen services with Artificial Intelligence. She also leads a meetup community based out of New York to help educate public sector employees via hands on labs and discussions. Apart from her passion for learning new technologies and innovating with AI, she is a sports enthusiast, a great badminton player and enjoys playing Billiards. Find her on LinkedIn at https: //www.linkedin.com/in/priyanshi-singh5/