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)

Review questions and exercises

  1. What does cloud mean?
  2. What does cloud computing mean?
  3. Why do we care about sharing our working environments with others?
  4. How do we register on Anaconda Cloud?
  5. Do users need an account to use the Anaconda Cloud platform?
  6. How do we upload our notebook to Anaconda Cloud?
  7. Why is it important to share our projects?
  8. How do you share your project? Build a project and share it with someone else.
  9. How do you recreate your partner's Anaconda environment?
  10. What is the meaning of the following two command lines:
conda remove --name myenv -all 
conda info -envs 
  1. How can we launch a Jupyter QtConsole?
  2. Run a Jupyter notebook called Octave Maric.ipynb under the subdirectory of examples/Builtin Extension. Note that you have to find a way to install a package called octavemagic first.
  3. Share your environment with another person to see the effect.
  4. Generate a set...