Hands-On Data Science with Anaconda: Utilize the right mix of tools to create high-performance data science applications
By 作者: Dr. Yuxing Yan – James Yan
ISBN-10 书号: 1788831195
ISBN-13 书号: 9781788831192
Release Finelybook 出版日期: 2018-05-31
pages 页数: (364 )

$34.99


Book Description to Finelybook sorting

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.

Contents
1: ECOSYSTEM OF ANACONDA
2: ANACONDA INSTALLATION
3: DATA BASICS
4: DATA VISUALIZATION
5: STATISTICAL MODELING IN ANACONDA
6: MANAGING PACKAGES
7: OPTIMIZATION IN ANACONDA
8: UNSUPERVISED LEARNING IN ANACONDA
9: SUPERVISED LEARNING IN ANACONDA
10: PREDICTIVE DATA ANALYTICS – MODELING AND VALIDATION
11: ANACONDA CLOUD
12: DISTRIBUTED COMPUTING, PARALLEL COMPUTING, AND HPCC
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
Authors
Dr. Yuxing Yan
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 six books. Two of his recent publications are Python for Finance and Financial Modeling 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
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.

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