Learning Predictive Analytics with R.
R data analysis projects : build end to end analytics systems to get deeper insights from your data /
R data mining : implement data mining techniques through practical use cases and real-world datasets /
Introducción a la ciencia de datos en R : un enfoque práctico /
Empezando a transformar bases de datos con R y dplyr
Jupyter Cookbook : Over 75 recipes to perform interactive computing across Python, R, Scala, Spark, JavaScript, and more.
Mastering Predictive Analytics with Scikit-Learn and TensorFlow : Implement Machine Learning Techniques to Build Advanced Predictive Models Using Python.
Big data analytics with Java : big data analytics - massive, predictive, social and self-driving /
Python 3 and data analytics : pocket primer /
SQL for Data Analytics : Perform Fast and Efficient Data Analysis with the Power of SQL.
Dēta bunseki to dēta saiensu /
Pandas 1.x cookbook : practical recipes for scientific computing, time series analysis and exploratory data analysis using Python /
Mastering Java for data science : building data science applications in Java /
Learning Google BigQuery : a beginner's guide to mining massive datasets through interactive analysis /
Hands-on web scraping with Python : perform advanced scraping operations using various Python libraries and tools such as Selenium, Regex, and others /
Python Data Mining Quick Start Guide : a Beginner's Guide to Extracting Valuable Insights from Your Data.
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 programming fundamentals : deal with data using various modeling techniques /
Hands-on data analysis with Pandas : efficiently perform data collection, wrangling, analysis, and visualization using Python /
Oracle Information integration, migration, and consolidation : the definitive guide to information integration and migration in a heterogeneous world : use Oracle technologies and best practices to manage, maintain, migrate, and mobilize data /
Mastering machine learning with R : advanced prediction, algorithms, and learning methods with R 3.x /
Applied data visualization with R and ggplot2 : Create useful, elaborate, and visually appealing plots /
A Primer in Biological Data Analysis and Visualization Using R
R Graph essentials : use R's powerful graphing capabilities to design and create professional-level graphics /
Modern R programming cookbook : recipes to simplify your statistical applications /
R for data science /
Mastering R for quantitative finance : use R to optimize your trading strategy and build up your own risk management system /
Learning probabilistic graphical models in R : familiarize yourself with probabilistic graphical models through real-world problems and illustrative code examples in R /
Learning Bayesian models with R : become an expert in Bayesian machine learning methods using R and apply them to solve real-world big data problems /
Shin kango, rihabiri, fukushi no tame no Excel to R o tsukatta tōkeigaku /
Seimei kagaku, seibutsu kōgaku no tame no machigai kara manabu jissen tōkei kaiseki : R, Python ni yoru dēta shori kotohajime /
Ecological models and data in R /
A Primer in Biological Data Analysis and Visualization Using R.
Learning Quantitative Finance with R.
A step-by-step guide to exploratory factor analysis with R and Rstudio /
A primer in biological data analysis and visualization using R /
Knowledge mining using intelligent agents /
Agent-based computing /
Active mining : new directions of data mining /
Hands-on data science and Python machine learning : perform data mining and machine learning efficiently using Python and Spark /
Clinical data-mining in an allied health organisation : a real world experience /
Clinical data as the basic staple of health learning : creating and protecting a public good : workshop summary /
Transforming healthcare with big data and AI /
Adaptive web sites : a knowledge extraction from web data approach /
Principles of data science : learn the techniques and math you need to start making sense of your data /
Data Science with Python : Combine Python with Machine Learning Principles to Discover Hidden Patterns in Raw Data.
Java data mining : strategy, standard, and practice : a practical guide for architecture, design, and implementation /
Applied data analytics : principles and applications /
Reality mining : using big data to engineer a better world /
Nonlinear integrals and their applications in data mining /
Data wrangling with Python : creating actionable data from raw sources /
Biological data mining and its applications in healthcare /
Big data visualization : learn effective tools and techniques to separate big data into manageable and logical components for efficient data visualization /
Mastering predictive analytics with R : machine learning techniques for advanced models /