Book Image

Hands-On Data Science with Anaconda

By : Yuxing Yan, James Yan
Book Image

Hands-On Data Science with Anaconda

By: Yuxing Yan, James 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)

Anaconda Cloud

In Chapter 2, Anaconda Installation, we'll explain this in more detail. This function is used to collaborate with different users or group members. For example, we have a small group of ten developers working on the same project. For this reason, we have to share our programs, command datasets, and working environments, and we could use Anaconda Cloud to do so. After going to https://anaconda.org/, we will be directed to the Anaconda home page.

Note that users have to register with Anaconda before they can use this function. For example, one of the authors has the link https://anaconda.org/paulyan/dashboard. After we register, we can see the following:

Later in the book, we devote a whole chapter to this.