Seimei kagaku, seibutsu kōgaku no tame no machigai kara manabu jissen tōkei kaiseki : R, Python ni yoru dēta shori kotohajime /

Shin kango, rihabiri, fukushi no tame no Excel to R o tsukatta tōkeigaku /

R data mining : implement data mining techniques through practical use cases and real-world datasets /

Empezando a transformar bases de datos con R y dplyr

Introducción a la ciencia de datos en R : un enfoque práctico /

Become a Python data analyst : perform exploratory data analysis and gain insight into scientific computing using Python /

Python 3 and data analytics : pocket primer /

Big data analytics with Java : big data analytics - massive, predictive, social and self-driving /

Jupyter Cookbook : Over 75 recipes to perform interactive computing across Python, R, Scala, Spark, JavaScript, and more.

Mastering Java for data science : building data science applications in Java /

Using OpenRefine : the essential OpenRefine guide that takes you from data analysis and error fixing to linking your dataset to the Web /

Hands-On Data Analysis with Scala : Perform Data Collection, Processing, Manipulation, and Visualization with Scala.

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 /

Hands-on web scraping with Python : perform advanced scraping operations using various Python libraries and tools such as Selenium, Regex, and others /

SQL for Data Analytics : Perform Fast and Efficient Data Analysis with the Power of SQL.

Python Data Mining Quick Start Guide : a Beginner's Guide to Extracting Valuable Insights from Your Data.

R data analysis projects : build end to end analytics systems to get deeper insights from your data /

Data wrangling with Python : creating actionable data from raw sources /

Mastering predictive analytics with R : machine learning techniques for advanced models /

Pandas 1.x cookbook : practical recipes for scientific computing, time series analysis and exploratory data analysis using Python /

Visions of STS : counterpoints in science, technology, and society studies /

The humanistic background of science /

Meaningful urban education reform : confronting the learning crisis in mathematics and science /

Hot science, high water : assembling nature, society and environmental policy in contemporary Vietnam /

Critical issues and bold visions for science education : the road ahead /

Grasping reality : an interpretation-realistic epistemology /

Safety in the elementary science classroom /

The power of argumentation /

Is theology a science? : the nature of the scientific enterprise in the scientific theology of Thomas Forsyth Torrance and the anarchic epistemology of Paul Feyerabend /

Assessing science understanding : a human constructivist view /

Civilisation : its cause and cure and other essays /

Physics and politics in revolutionary Russia /

Talking nets : an oral history of neural networks /

Integrating the Sciences and Society : Challenges, Practices, and Potentials /

Ensino Experimental das Ciências : um guia para professores do ensino Secundário : biologia e geologia /

The outlook for science and technology, 1985 /

Science without myth : on constructions, reality, and social knowledge /

The black doctors of colonial Lima : science, race, and writing in colonial and early Republican Peru /

Science and the university /

Albert Einstein, historical and cultural perspectives : the centennial symposium in Jerusalem /

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 /

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 /

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 /

Mastering Predictive Analytics with Scikit-Learn and TensorFlow : Implement Machine Learning Techniques to Build Advanced Predictive Models Using Python.

Applied data analytics : principles and applications /

Reality mining : using big data to engineer a better world /

Nonlinear integrals and their applications in data mining /

Pandas 1.x cookbook : practical recipes for scientific computing, time series analysis and exploratory data analysis using Python /

Data wrangling with Python : creating actionable data from raw sources /

Biological data mining and its applications in healthcare /

Dēta bunseki to dēta saiensu /