Analiza danych

Analiza danych jest ekscytującą dyscypliną, która umożliwia zrozumienie pewnych zjawisk, uzyskanie wglądu i wiedzy na podstawie surowych danych. Pojęcie to oznacza dokładnie przetwarzanie danych za pomocą technik matematycznych i statystycznych w celu uzyskania cennych wniosków, podjęcia ważnych decyzji i opracowania przydatnych produktów. Termin ten wywodzi się od angielskiego data science, często traktowanego jako synonim takich terminów, jak analityka biznesowa, badania operacyjne, business intelligence, wywiad konkurencyjny, analiza i modelowanie danych, a także pozyskiwanie wiedzy. Dzięki takim technologiom, jak języki Python czy R, platformy Hadoop i Spark masz szansę wyciągnąć maksimum wniosków, dostrzec szanse na rozwój swojej organizacji albo przewidzieć i zapobiec zagrożeniom.

siatka lista

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. Click here to enter text

Tony Fischetti, Brett Lantz, Jaynal Abedin, Hrishi...

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

Kuntal Ganguly, Shanthi Viswanathan, Viswa Viswanathan

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

Gopi Subramanian

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

Andrea Cirillo

R Data Science Essentials. R Data Science Essentials

Raja B. Koushik, Sharan Kumar Ravindran

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

Atmajitsinh Gohil, Atmajitsingh Gohil

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

Vitor Bianchi Lanzetta

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

Yu-Wei, Chiu (David Chiu)

R Graph Essentials

David Lillis, David A Lillis

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

Jaynal Abedin, Jaynal Abedin, Hrishi Mittal

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

Dipanjan Sarkar, Raghav Bali

R: Mining spatial, text, web, and social media data. Create and customize data mining algorithms

Nathan H. Danneman, Richard Heimann, Pradeepta Mishra,...

R Programming Fundamentals. Deal with data using various modeling techniques

Kaelen Medeiros

R: Recipes for Analysis, Visualization and Machine Learning. Click here to enter text

Shanthi Viswanathan, Atmajitsinh Gohil, Viswa Viswanathan, Yu-Wei,...

R Statistics Cookbook. Over 100 recipes for performing complex statistical operations with R 3.5

Francisco Juretig

R: Unleash Machine Learning Techniques. Smarter data analytics

Brett Lantz, Cory Lesmeister, Dipanjan Sarkar, Raghav...

R Web Scraping Quick Start Guide. Techniques and tools to crawl and scrape data from websites

Olgun Aydin

Raportowanie w System Center Configuration Manager Bez tajemnic

Garth Jones, Dan Toll, Kerrie Meyler

Reactive Programming in Kotlin. Design and build non-blocking, asynchronous Kotlin applications with RXKotlin, Reactor-Kotlin, Android, and Spring

Rivu Chakraborty

Real-Time Big Data Analytics. Design, process, and analyze large sets of complex data in real time

Sumit Gupta, Shilpi Saxena

Redash v5 Quick Start Guide. Create and share interactive dashboards using Redash

Alexander Leibzon, Yael Leibzon