Publisher: K-i-s-publishing

grid list

R Data Mining. Implement data mining techniques through practical use cases and real-world datasets

Enrico Pegoraro, Andrea Cirillo

R Data Science Essentials. R Data Science Essentials

Raja B. Koushik, Sharan Kumar Ravindran

R Data Structures and Algorithms. Increase speed and performance of your applications with effi cient data structures and algorithms

PKS Prakash, Achyutuni Sri Krishna Rao

R Data Visualization Cookbook. Over 80 recipes to analyze data and create stunning visualizations with R

Atmajitsinh Gohil

R Data Visualization Recipes. A cookbook with 65+ data visualization recipes for smarter decision-making

Vitor Bianchi Lanzetta

R Deep Learning Cookbook. Solve complex neural net problems with TensorFlow, H2O and MXNet

PKS Prakash, Achyutuni Sri Krishna Rao

R Deep Learning Essentials. A step-by-step guide to building deep learning models using TensorFlow, Keras, and MXNet - Second Edition

Mark Hodnett, Joshua F. Wiley

R Deep Learning Projects. Master the techniques to design and develop neural network models in R

Yuxi (Hayden) Liu, Pablo Maldonado

R for Data Science Cookbook. Over 100 hands-on recipes to effectively solve real-world data problems using the most popular R packages and techniques

Prabhanjan Narayanachar Tattar, Yu-Wei, Chiu (David Chiu)

R for Data Science. Learn and explore the fundamentals of data science with R

Toomey

R Graph Essentials

R Graphs Cookbook Second Edition. Over 70 recipes for building and customizing publication-quality visualizations of powerful and stunning R graphs - Second Edition

Jaynal Abedin, Hrishi V. Mittal

R High Performance Programming. Overcome performance difficulties in R with a range of exciting techniques and solutions

Aloysius Shao Qin Lim, Tjhi W Chandra

R Machine Learning By Example. Understand the fundamentals of machine learning with R and build your own dynamic algorithms to tackle complicated real-world problems successfully

Raghav Bali

R Machine Learning Essentials. Gain quick access to the machine learning concepts and practical applications using the R development environment

Michele Usuelli

R Machine Learning Projects. Implement supervised, unsupervised, and reinforcement learning techniques using R 3.5

Dr. Sunil Kumar Chinnamgari