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Hands-On Data Science with Anaconda: Utilize the right mix of tools to create high-performance data science applications

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Develop, deploy, and streamline your data science projects with the most popular end-to-end platform, Anaconda

Key Features

  • Use Anaconda to find solutions for clustering, classification, and linear regression
  • Analyze your data efficiently with the most powerful data science stack
  • Use the Anaconda cloud to store, share, and discover projects and libraries

Book Description

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.

What you will learn

  • Perform cleaning, sorting, classification, clustering, regression, and dataset modeling using Anaconda
  • Use the package manager conda and discover, install, and use functionally efficient and scalable packages
  • Get comfortable with heterogeneous data exploration using multiple languages within a project
  • Perform distributed computing and use Anaconda Accelerate to optimize computational powers
  • Discover and share packages, notebooks, and environments, and use shared project drives on Anaconda Cloud
  • Tackle advanced data prediction problems

Who This Book Is For

Hands-On Data Science with Anaconda is for you if you are a developer who is looking for the best tools in the market to perform data science. It's also ideal for data analysts and data science professionals who want to improve the efficiency of their data science applications by using the best libraries in multiple languages. Basic programming knowledge with R or Python and introductory knowledge of linear algebra is expected.

Table of Contents

  1. Ecosystem of Anaconda
  2. Anaconda Installation
  3. Data basics
  4. Data visualization
  5. Statistics modeling in Anaconda
  6. Managing packages
  7. Optimization in Anaconda
  8. Unsupervised Learning in Anaconda
  9. Supervised Learning in Anaconda
  10. Predictive Data Analytics: Modelling and Validation
  11. Anaconda Cloud
  12. Distributed computing, parallel computing and HPCC
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