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)

Understanding predictive data analytics

In terms of future events, people could have many questions. For an investor, if he/she could predict the future movement of a stock price, he/she could make more profit. For a company, if they could forecast the trend of their products, they could increase their stock price and products' market shares. For governments, if they could predict the impact of an aging population on society and the economy, they would have more incentive to design a better policy in terms of government budget and other related strategic decisions.

For universities, if they could have a good grasp of the market demand in terms of quality and skill sets for their graduates, they could design a set of better programs or launch new programs to satisfy the future needs in terms of a labor force.

For a better prediction or forecast, researchers have to consider...