
Proceedings of the Global AI Congress 2019
Jyotsna Kumar Mandal, Somnath Mukhopadhyay
Published 2020
729 pages
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.

Jyotsna Kumar Mandal, Somnath Mukhopadhyay
Published 2020
729 pages

Joshua N. Milligan
Published 2020
576 pages

Ram Shringar Rao, Nanhay Singh, Omprakash Kaiwartya, Sanjoy Das
Published 2020
300 pages

Ai Publishing
Published 2020
252 pages

Hitachi and The University of Tokyo Lab
Published 2020
177 pages

Rajshree Srivastava, Pradeep Kumar Mallick, Siddhartha Swarup Rautaray, Manjusha Pandey
Published 2020
331 pages

Tania Peitzker
Published 2020
170 pages

Sauro Pierucci, Flavio Manenti, Giulia Luisa Bozzano, Davide Manca
Published 2020
2112 pages

Yichuan Zhao, Ding-Geng (Din) Chen
2020 · 2021 edition
509 pages

Arni S. R. Srinivasa Rao, C. R. Rao
Published 2020
898 pages

Satchidananda Dehuri, Sujata Dash, Ruppa K. Thulasiram, Rohen H. Singh, Margarita Favorskaya
2020 · 2023 edition
735 pages

Xingni Zhou, China Science Publishing &. Media China Science Publishing & Media Ltd
Published 2020
371 pages

Nailong Zhang
Published 2020
216 pages

Darnell Blank
Published 2020
116 pages

K. R. Venugopal, K. C. Srikantaiah, Sejal Santosh Nimbhorkar
Published 2020
188 pages

Dijiang Huang, Qiuxiang Dong, Yan Zhu
Published 2020
309 pages

Steve Hoberman
Published 2020
180 pages

Nicolae Tarla
Published 2020
644 pages

Kazuo Wada
Published 2020
166 pages

Ananda S. Prasad, George J. Brewer
Published 2020
326 pages

Svetlana Igorevna Ashmarina, Valentina Vyacheslavovna Mantulenko
Published 2020
864 pages

Hua Wang, Jinli Cao, Yanchun Zhang
2020 · 2021 edition
300 pages

Giovanni Leucci
Published 2020
314 pages

Rosemary Mitchell-Schuitevoerder
Published 2020
164 pages