Springer just released 65 books related to Machine Learning

The 65 books list:

The Elements of Statistical Learning

Trevor Hastie, Robert Tibshirani, Jerome Friedman

Introductory Time Series with R

Paul S.P. Cowpertwait, Andrew V. Metcalfe

A Beginner’s Guide to R

Alain Zuur, Elena N. Ieno, Erik Meesters

Introduction to Evolutionary Computing

A.E. Eiben, J.E. Smith

Data Analysis

Siegmund Brandt

Linear and Nonlinear Programming

David G. Luenberger, Yinyu Ye

Introduction to Partial Differential Equations

David Borthwick

Fundamentals of Robotic Mechanical Systems

Jorge Angeles

Data Structures and Algorithms with Python

Kent D. Lee, Steve Hubbard

Introduction to Partial Differential Equations

Peter J. Olver

Methods of Mathematical Modelling

Thomas Witelski, Mark Bowen

LaTeX in 24 Hours

Dilip Datta

Introduction to Statistics and Data Analysis

Christian Heumann, Michael Schomaker, Shalabh

Principles of Data Mining

Max Bramer

Computer Vision

Richard Szeliski

Data Mining

Charu C. Aggarwal

Computational Geometry

Mark de Berg, Otfried Cheong, Marc van Kreveld, Mark Overmars

Robotics, Vision and Control

Peter Corke

Statistical Analysis and Data Display

Richard M. Heiberger, Burt Holland

Statistics and Data Analysis for Financial Engineering

David Ruppert, David S. Matteson

Stochastic Processes and Calculus

Uwe Hassler

Statistical Analysis of Clinical Data on a Pocket Calculator

Ton J. Cleophas, Aeilko H. Zwinderman

Clinical Data Analysis on a Pocket Calculator

Ton J. Cleophas, Aeilko H. Zwinderman

The Data Science Design Manual

Steven S. Skiena

An Introduction to Machine Learning

Miroslav Kubat

Guide to Discrete Mathematics

Gerard O’Regan

Introduction to Time Series and Forecasting

Peter J. Brockwell, Richard A. Davis

Multivariate Calculus and Geometry

Seán Dineen

Statistics and Analysis of Scientific Data

Massimiliano Bonamente

Modelling Computing Systems

Faron Moller, Georg Struth

Search Methodologies

Edmund K. Burke, Graham Kendall

Linear Algebra Done Right

Sheldon Axler

Linear Algebra

Jörg Liesen, Volker Mehrmann

Algebra

Serge Lang

Understanding Analysis

Stephen Abbott

Linear Programming

Robert J Vanderbei

Understanding Statistics Using R

Randall Schumacker, Sara Tomek

An Introduction to Statistical Learning

Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani

Statistical Learning from a Regression Perspective

Richard A. Berk

Applied Partial Differential Equations

J. David Logan

Robotics

Bruno Siciliano, Lorenzo Sciavicco, Luigi Villani, Giuseppe Oriolo

Regression Modeling Strategies

Frank E. Harrell , Jr.

A Modern Introduction to Probability and Statistics

F.M. Dekking, C. Kraaikamp, H.P. Lopuhaä, L.E. Meester

The Python Workbook

Ben Stephenson

Machine Learning in Medicine — a Complete Overview

Ton J. Cleophas, Aeilko H. Zwinderman

Object-Oriented Analysis, Design and Implementation

Brahma Dathan, Sarnath Ramnath

Introduction to Data Science

Laura Igual, Santi Seguí

Applied Predictive Modeling

Max Kuhn, Kjell Johnson

Python For ArcGIS

Laura Tateosian

Concise Guide to Databases

Peter Lake, Paul Crowther

Digital Image Processing

Wilhelm Burger, Mark J. Burge

http://link.springer.com/openurl?genre=book&isbn=978-1-4471-6684-9

Bayesian Essentials with R

Jean-Michel Marin, Christian P. Robert

http://link.springer.com/openurl?genre=book&isbn=978-1-4614-8687-9

Robotics, Vision and Control

Peter Corke

http://link.springer.com/openurl?genre=book&isbn=978-3-642-20144-8

Foundations of Programming Languages

Kent D. Lee

http://link.springer.com/openurl?genre=book&isbn=978-3-319-70790-7

Introduction to Artificial Intelligence

Wolfgang Ertel

http://link.springer.com/openurl?genre=book&isbn=978-3-319-58487-4

Introduction to Deep Learning

Sandro Skansi

http://link.springer.com/openurl?genre=book&isbn=978-3-319-73004-2

Linear Algebra and Analytic Geometry for Physical Sciences

Giovanni Landi, Alessandro Zampini

http://link.springer.com/openurl?genre=book&isbn=978-3-319-78361-1

Applied Linear Algebra

Peter J. Olver, Chehrzad Shakiban

http://link.springer.com/openurl?genre=book&isbn=978-3-319-91041-3

Neural Networks and Deep Learning

Charu C. Aggarwal

http://link.springer.com/openurl?genre=book&isbn=978-3-319-94463-0

Data Science and Predictive Analytics

Ivo D. Dinov

http://link.springer.com/openurl?genre=book&isbn=978-3-319-72347-1

Analysis for Computer Scientists

Michael Oberguggenberger, Alexander Ostermann

http://link.springer.com/openurl?genre=book&isbn=978-3-319-91155-7

Excel Data Analysis

Hector Guerrero

http://link.springer.com/openurl?genre=book&isbn=978-3-030-01279-3

A Beginners Guide to Python 3 Programming

John Hunt

http://link.springer.com/openurl?genre=book&isbn=978-3-030-20290-3

Advanced Guide to Python 3 Programming

John Hunt

http://link.springer.com/openurl?genre=book&isbn=978-3-030-25943-3

Source : towardsdatascience

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