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Hands-On Data Science with Anaconda

Hands-On Data Science with Anaconda

By : Yuxing Yan, Yan
2.6 (5)
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Hands-On Data Science with Anaconda

Hands-On Data Science with Anaconda

2.6 (5)
By: Yuxing Yan, Yan

Overview of this book

Anaconda is an open source platform that brings together the best tools for data science professionals with more than 100 popular packages supporting Python, Scala, and R languages. Hands-On Data Science with Anaconda gets you started with Anaconda and demonstrates how you can use it to perform data science operations in the real world. The book begins with setting up the environment for Anaconda platform in order to make it accessible for tools and frameworks such as Jupyter, pandas, matplotlib, Python, R, Julia, and more. You’ll walk through package manager Conda, through which you can automatically manage all packages including cross-language dependencies, and work across Linux, macOS, and Windows. You’ll explore all the essentials of data science and linear algebra to perform data science tasks using packages such as SciPy, contrastive, scikit-learn, Rattle, and Rmixmod. Once you’re accustomed to all this, you’ll start with operations in data science such as cleaning, sorting, and data classification. You’ll move on to learning how to perform tasks such as clustering, regression, prediction, and building machine learning models and optimizing them. In addition to this, you’ll learn how to visualize data using the packages available for Julia, Python, and R.
Table of Contents (15 chapters)
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Task views for R

A task view is a set of R packages grouped by one or more experts around a specific topic. For example, for data visualization, we could choose the task view called Graphics. For a text analysis, we could choose the NaturalLanguageAnalysis task view. To find a list of all these task views, we can go to the R home page at http://r-project.org. After clicking CRAN, choose a mirror server, then click Task Views on the left-hand side. The following screen will be displayed:

If we are interested in data visualization, then we can click on Graphics (see the following screenshot):

To save space, only the top part is shown. The task view gives many R-related packages around the topics of Graphic Display & Visualization. Another great benefit is installing all related packages by issuing just three lines of R code. Assume that we are interested in the task view related...

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