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

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.

1128010907
Hands-On Data Science with Anaconda: Utilize the right mix of tools to create high-performance data science applications

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.

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

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

by Dr. Yuxing Yan, James Yan
Hands-On Data Science with Anaconda: Utilize the right mix of tools to create high-performance data science applications

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

by Dr. Yuxing Yan, James Yan

eBook

$29.99 

Available on Compatible NOOK devices, the free NOOK App and in My Digital Library.
WANT A NOOK?  Explore Now

Related collections and offers


Overview

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.


Product Details

ISBN-13: 9781788834735
Publisher: Packt Publishing
Publication date: 05/31/2018
Sold by: Barnes & Noble
Format: eBook
Pages: 364
File size: 14 MB
Note: This product may take a few minutes to download.

About the Author

Dr. Yuxing Yan graduated from McGill University with a PhD in finance. He has taught various finance courses at eight universities in Canada, Singapore, and the U.S. He has published 23 research and teaching-related papers and is the author of 6 books. Two of his recent publications are Python for Finance and Financial Modelling using R. He is well-versed in R, Python, SAS, MATLAB, Octave, and C. In addition, he is an expert on financial data analytics.

James Yan is an undergraduate student at the University of Toronto (UofT), currently double-majoring in computer science and statistics. He has hands-on knowledge of Python, R, Java, MATLAB, and SQL. During his study at UofT, he has taken many related courses, such as Methods of Data Analysis I and II, Methods of Applied Statistics, Introduction to Databases, Introduction to Artificial Intelligence, and Numerical Methods, including a capstone course on AI in clinical medicine.

Table of Contents

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
From the B&N Reads Blog

Customer Reviews