Product Analytics
Joanne Rodrigues
Published 2020
400 pages
The most popular data science books of 2020
Data science books show you how to learn from data. Statistics, databases, visualization and machine learning are taught through practical examples, usually with code. Beginners will find gentle introductions and working analysts will find deeper references. Good reading for a career change, too. This list shows the ones first published in 2020.
Results
Hands On With Google Data Studio
Lee Hurst
Published 2020
432 pages
Pandas 1.x Cookbook
Matt Harrison, Theodore Petrou
Published 2020
626 pages
Learn Kubernetes Security
Kaizhe Huang, Pranjal Jumde
2020 · 4402 edition
330 pages
Designing Digital Products for Kids
Rubens Cantuni
Published 2020
354 pages
Graph Databases in Action
Josh Perryman, Dave Bechberger
Published 2020
366 pages
Understanding Artificial Intelligence
Nicolas Sabouret
Published 2020
160 pages
Artificial Intelligence in Finance A Python-based Guide
Yves J. Hilpisch
Published 2020
455 pages
Innovative Tableau 100 More Tips, Tutorials, and Strategies
Ryan Sleeper
Published 2020
615 pages
Machine Learning and Data Science Blueprints for Finance
Hariom Tatsat, Sahil Puri, Brad Lookabaugh
Published 2020
434 pages
Probabilistic Deep Learning
Oliver Duerr, Beate Sick, Elvis Murina
Published 2020
296 pages
A Hands-On Introduction to Data Science
Chirag Shah
Published 2020
424 pages
Python Scripting for ArcGIS Pro
Paul A. Zandbergen
2020 · 2025 edition
414 pages
Hands-On Exploratory Data Analysis with Python
Suresh Kumar Mukhiya, Usman Ahmed
Published 2020
352 pages
Big Data on Campus
Karen L. Webber, Henry Y. Zheng
Published 2020
336 pages
Hypothesis Testing An Intuitive Guide for Making Data Driven Decisions
Jim Frost
2020 · 2024 edition
390 pages
Mastering Large Datasets with Python Parallelize and Distribute Your Python Code
John T. Wolohan
Published 2020
312 pages
The Infographic A History of Data Graphics in News and Communications
Murray Dick
Published 2020
248 pages
Representation Learning for Natural Language Processing
Zhiyuan Liu, Yankai Lin, Maosong Sun
2020 · 2023 edition
521 pages
Hands-On Machine Learning with ML.NET
Jarred Capellman
Published 2020
296 pages
Digital Marketing Analytics
Kevin Hartman
Published 2020
241 pages
Process Mining in Action
Lars Reinkemeyer
2020 · 2021 edition
232 pages
Python Feature Engineering Cookbook Over 70 Recipes for Creating, Engineering, and Transforming Features to Build Machine Learning Models
Soledad Galli
Published 2020
372 pages
Machine Learning with R, the tidyverse, and mlr
Hefin I. Rhys
Published 2020
536 pages