predictive analytics hr

Microsoft Power Bi Data Analyst Associate Study Guide - by Paul Turley (Paperback)

97 Things Every Data Engineer Should Know - by Tobias Macey (Paperback)

Learning SQL - 3rd Edition,Annotated by Alan Beaulieu (Paperback)

Learning Ray - by Max Pumperla & Edward Oakes & Richard Liaw (Paperback)

Data Science Programming All-In-One for Dummies - by John Paul Mueller & Luca Massaron (Paperback)

Murach's Python for Data Analysis - by Scott McCoy (Paperback)

Data Science - by Herbert Jones (Hardcover)

R in Action, Third Edition - by Robert I Kabacoff (Paperback)

Data Structures and Program Design Using Java - by Dheeraj Malhotra & Neha Malhotra (Paperback)

Microsoft Power Bi for Dummies - 2nd Edition by Jack A Hyman (Paperback)

Root Cause Analysis - 2nd Edition by Duke Okes (Paperback)

High Performance Spark - 2nd Edition by Holden Karau & Adi Polak & Rachel Warren (Paperback)

Marketing Metrics - 2nd Edition by Christina Inge

Principles and Theory for Data Mining and Machine Learning - (Springer Statistics) by Bertrand Clarke & Ernest Fokoue & Hao Helen Zhang

The Data Science Design Manual - (Texts in Computer Science) by Steven S Skiena (Hardcover)

Learning PySpark - by Denny Lee & Tomasz Drabas (Paperback)

Information-Statistical Data Mining - (The Springer International Engineering and Computer Science) by Bon K Sy & Arjun K Gupta (Hardcover)

Frictionless Data - by Zane Hall

Deep Learning - by Josh Patterson & Adam Gibson (Paperback)

Data Quality Fundamentals - by Barr Moses & Lior Gavish & Molly Vorwerck (Paperback)

Practical Python Data Wrangling and Data Quality - by Susan E McGregor (Paperback)

Statistics Every Programmer Needs - by Gary Sutton (Paperback)

Deep Reinforcement Learning in Action - by Alexander Zai & Brandon Brown (Paperback)

Data Quality Engineering in Financial Services - by Brian Buzzelli (Paperback)