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Publisher: 8

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Henryk Sienkiewicz

Henryk Sienkiewicz

Quo vadis? A Narrative of the Time of Nero

Henryk Sienkiewicz

Quo Vadis. A Narrative of the Time of Nero

Henryk Sienkiewicz

Quo vadis? Henryka Sienkiewicza. Od legendy do arcydzieła

Teresa Świętosławska

Quo vadis, Rosjo? Spojrzenie ambasadora Niemiec

Ruediger von Fritsch

Andrzej Dragan

Andrzej Dragan

Quodlibet [co się podoba]. Studia dominikańskie

Praca zbiorowa

R Bioinformatics Cookbook. Use R and Bioconductor to perform RNAseq, genomics, data visualization, and bioinformatic analysis

Dan MacLean

R Bioinformatics Cookbook. Utilize R packages for bioinformatics, genomics, data science, and machine learning - Second Edition

Dan MacLean

R: Data Analysis and Visualization. Master the art of building analytical models using R

Tony Fischetti, Brett Lantz, Hrishi V. Mittal,...

R Data Analysis Cookbook, Second Edition. Customizable R Recipes for data mining, data visualization and time series analysis - Second Edition

Kuntal Ganguly, Davor Lozić, Mzabalazo Z. Ngwenya,...

R Data Analysis Projects. Build end to end analytics systems to get deeper insights from your data

Mark Hodnett, Gopi Subramanian

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