Call Number (LC) | Title | Results |
---|---|---|
QA276.45.M56 S58 2012 | Minitab demystified / | 1 |
QA276.45.P98 D46 2021 | Applied univariate, bivariate, and multivariate statistics using Python / | 1 |
QA276.45.R3 |
25 recipes for getting started with R / R All-in-One / Efficient data processing with R / Advanced R statistical programming and data models : analysis, machine learning, and visualization / R quick syntax reference / CRAN recipes : DPLYR, Stringr, Lubridate, and RegEx in R / Da gui mo shu ju fen xi he jian mo : ji yu Spark yu R = Mastering Spark with R / R in action : data analysis and graphics with R and Tidyverse / Beginning R : an introduction to statistical programming / R programming / R Data Science Quick Reference : a Pocket Guide to APIs, Libraries, and Packages / R programming for statistics and data science / R jin nang miao ji = R cookbook / Advanced R 4 data programming and the cloud : using PostgreSQL, AWS, and Shiny / The R book / Using R to unlock the value of big data : big data analytics with Oracle R Enterprise and Oracle R Connector for Hadoop / Advanced Object-Oriented Programming in R : Statistical Programming for Data Science, Analysis and Finance / The essential R reference / Graphing data with R : an introduction / Text mining with R : a tidy approach / Understanding and applying basic statistical methods using R / Reproducible research and reports with R Markdown : how to streamline your reporting workflow in R / R graphics cookbook : practical recipes for visualizing data / Advanced R : data programming and the cloud / R for Microsoft Excel users : making the transition for statistical analysis / Machine learning with R : discover how to build machine learning algorithms, prepare data, and dig deep into data prediction techniques with R / R for data science : import, tidy, transform, visualize, and model data / Introduction to Shiny : learn how to build interactive web apps with R, Shiny, and reactive programming / Learning shiny : make the most of R's dynamic capabilities and create web applications with Shiny / Easy, reproducible report with R / Mastering predictive analytics with R : master the craft of predictive modeling by developing strategy, intuition, and a solid foundation in essential concepts / R projects for dummies / Practical data science with R : video edition / R für Data Science : Daten importieren, bereinigen, umformen, modellieren und visualisieren / Business case analysis with R : simulation tutorials to support complex business decisions / Expert data wrangling with R : streamline your work with tidyr, dplyr, and ggvis / Shiny R : LiveLessons / R programming by example : practical, hands-on projects to help you get started with R / Data manipulation with R and SQL : building effective, coherent, and streamlined data structures / R programming fundamentals / Functional data structures in R : advanced statistical programming in R / Programming skills for data science : start writing code to wrangle, analyze, and visualize data with R / Applied unsupervised learning with R / R statistics cookbook : over 100 recipes for performing complex statistical operations with R 3.5 / Data visualization in R with ggplot2 : creating effective and attractive data visualizations / R für Data Science : Daten importieren, bereinigen, umformen und visualisieren / R deep learning essentials : a step-by-step guide to building deep learning models using TensorFlow, Keras, and MXNet / R 4 quick syntax reference : a pocket guide to the language, API's and library / Shu ju ke xue zhi bian cheng ji shu : shi yong R jin xing shu ju qing li, fen xi yu ke shi hua / R : kurz & gut / R ultimate 2023 : R for data science and machine learning. Metaprogramming in R : advanced statistical programming for data science, analysis and finance / Statistik mit R Schnelleinstieg : R einfach lernen in 14 Tagen / R data analysis cookbook : a journey from data computation to data-driven insights / Machine learning with R cookbook : analyze data and build predictive models / Statistical application development with R and Python : power of statistics using R and Python / Learn R programming / Functional programming in R : advanced statistical programming for data science, analysis and finance / Learning quantitative finance with R : implement machine learning, time-series analysis, algorithmic trading and more / Mastering predictive analytics with R : machine learning techniques for advanced models / Statistik mit R : eine praxisorientierte Einführung in R / Multiple factor analysis by example using R / Advanced R / R 4 data science quick reference : a pocket guide to APIs. libraries, and packages / R-powered Excel for analytics / R recipes : a problem-solution approach / Introduction to data science with R : manipulating, visualizing, and modeling data with the R language / Advanced R programming. Writing great R code / R programming LiveLessons : fundamentals to advanced / Machine learning in R : automated algorithms for business analysis : applying K-Means clustering, decision trees, random forests, and neural networks / Mastering machine learning with R : advanced machine learning techniques for building smart applications with R 3.5 / Practical predictive analytics : back to the future with R, Spark, and more! / Efficient R programming : a practical guide to smarter programming / Efficient R optimization / Using R for big data with Spark : hands-on data analytics in the Cloud using Spark, AWS, SparkR, and more / Automated trading with R : quantitative research and platform development / R : predictive analysis : master the art of predictive modeling / Mastering Spark with R : the complete guide to large-scale analysis and modeling / Sams teach yourself R in 24 hours / Statistical data cleaning with applications in R / R kukku bukku / Practical R 4 : applying R to data manipulation, processing and integration / R PROGRAMMING FOR ACTUARIAL SCIENCE. R yu yan bian cheng zhi nan = Learning R programming / Liang hua jin rong R yu yan chu ji jiao cheng = Introduction to R for quantitative finance / Shen du xue xi shi zhan shou ce : R yu yan ban = R deep learning cookbook / R da shu ju fen xi shi yong zhi nan = Big data analytics with R / Gai lü tu mo xing : ji yu R yu yan = Learning probabilistic graphical models in R / Beginning data science in R 4 : data analysis, visualization, and modelling for the data scientist / Statistical analysis with R essentials / Basic statistics : an introduction with R / R Statistics Cookbook : Over 100 Recipes for Performing Complex Statistical Operations with R 3. 5 / R for data science / A Primer in Biological Data Analysis and Visualization Using R. Advanced deep learning with R : become an expert at designing, building, and improving advanced neural network models using R / Applied Unsupervised Learning with R : Uncover Hidden Relationships and Patterns with K-Means Clustering, Hierarchical Clustering, and PCA. The R software : fundamentals of programming and statistical analysis / Mastering R for quantitative finance : use R to optimize your trading strategy and build up your own risk management system / Introduction to R for quantitative finance : solve a diverse range of problems with R, one of the most powerful tools for quantitative finance / R data structures and algorithms : increase speed and performance of your applications with efficient data structures and algorithms / 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 / R data science essentials : learn the essence of data science and visualization using R in no time at all / Simulation for data science with R : harness actionable insights from your data with computational statistics and simulations using R / Big data analytics with R : utilize R to uncover hidden patterns in your big data / Learning probabilistic graphical models in R : familiarize yourself with probabilistic graphical models through real-world problems and illustrative code examples in R / Mastering text mining with R : master text-taming techniques and build effective text-processing applications with R / Hands-on data science with R : techniques to perform data manipulation and mining to build smart analytical models using R / Hands-on geospatial analysis with R and QGIS : a beginner's guide to manipulating, managing, and analyzing spatial data using R and QGIS 3.2.2 / R data analysis projects : build end to end analytics systems to get deeper insights from your data / Data analysis with R : a comprehensive guide to manipulating, analyzing, and visualizing data in R / Hands-on ensemble learning with R : a beginner's guide to combining the power of machine learning algorithms using ensemble techniques / R web scraping quick start guide : techniques and tools to crawl and scrape data from websites / Learn R for applied statistics : with data visualizations, regressions, and statistics / Business statistics with solutions in R / R : recipes for analysis, visualization and machine learning : get savvy with R language and actualize projects aimed at analysis, visualization and machine learning / |
118 |
QA276.45.R3 A34 2014 | R Graphs cookbook : over 70 recipes for building and customizing publication-quality visualizations of powerful and stunning R graphs / | 1 |
QA276.45.R3 A344 2010 | R in a nutshell / | 1 |
QA276.45.R3 A35 2010 | R in a nutshell / | 1 |
QA276.45.R3 A35 2012 | R in a nutshell / | 1 |
QA276.45.R3 A76 2015 | Humanities data in R : exploring networks, geospatial data, images, and text / | 1 |
QA276.45.R3 .B533 2014 | R object-oriented programming : a practical guide to help you learn and understand the programming techniques necessary to exploit the full power R / | 1 |
QA276.45.R3 B73 2007 | A first course in statistical programming with R / | 1 |
QA276.45.R3 B73 2008eb | A first course in statistical programming with R / | 1 |
QA276.45.R3 B73 2016 | A first course in statistical programming with R / | 1 |
QA276.45.R3 B76 2018 | Business case analysis with R : simulation tutorials to support complex business decisions / | 1 |
QA276.45.R3 B78 2015 | An introduction to R for spatial analysis & mapping / | 1 |
QA276.45.R3 C45 2012eb | Exploring everyday things with R and Ruby / | 1 |
QA276.45.R3 C484 2019 | R graphics cookbook / | 1 |
QA276.45.R3 .C533 2018 | Regression Analysis with R : Design and develop statistical nodes to identify unique relationships within data at scale. | 1 |
QA276.45.R3 C64 2008 | Statistics and data with R : an applied approach through examples / | 1 |
QA276.45.R3 C64 2008eb | Statistics and data with R : an applied approach through examples / | 1 |
QA276.45.R3 C68 2013 | Learning R / | 1 |