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We extract valuable insights from your data to help you understand what's happening, operate your business more efficiently, and make better data-driven decisions. 
 

Practical Data Science Cookbook

Data's value has grown exponentially in the past decade, with Big Data today being one of the biggest buzzwords in business and IT, and data scientist hailed as “the sexiest job of the 21st century.” Practical Data Science Cookbook helps you see beyond the hype and get past the theory by providing you with a hands-on exploration of data science. With a comprehensive range of recipes designed to help you learn fundamental data science tasks, you'll uncover practical steps to help you produce powerful insights into Big Data using R and Python.

Use this valuable data science book to discover tricks and techniques to get to grips with your data. Learn effective data visualization with an automobile fuel efficiency data project, analyze football statistics, learn how to create data simulations, and get to grips with stock market data to learn data modelling. Find out how to produce sharp insights into social media data by following data science tutorials that demonstrate the best ways to tackle Twitter data, and uncover recipes that will help you dive in and explore Big Data through movie recommendation databases.

Applied Text Analysis with Python

From news and speeches to informal chatter on social media, natural language is one of the richest and most underutilized sources of data. Not only does it come in a constant stream, always changing and adapting in context; it also contains information that is not conveyed by traditional data sources. The key to unlocking natural language is through the creative application of text analytics. This practical book presents a data scientist’s approach to building language-aware products with applied machine learning.

You’ll learn robust, repeatable, and scalable techniques for text analysis with Python, including contextual and linguistic feature engineering, vectorization, classification, topic modeling, entity resolution, graph analysis, and visual steering. By the end of the book, you’ll be equipped with practical methods to solve any number of complex real-world problems.

Data Analytics with Hadoop

Ready to use statistical and machine-learning techniques across large data sets? This practical guide shows you why the Hadoop ecosystem is perfect for the job. Instead of deployment, operations, or software development usually associated with distributed computing, you’ll focus on particular analyses you can build, the data warehousing techniques that Hadoop provides, and higher order data workflows this framework can produce.

Data scientists and analysts will learn how to perform a wide range of techniques, from writing MapReduce and Spark applications with Python to using advanced modeling and data management with Spark MLlib, Hive, and HBase. You’ll also learn about the analytical processes and data systems available to build and empower data products that can handle—and actually require—huge amounts of data.

Python Business Intelligence Cookbook

The amount of data produced by businesses and devices is going nowhere but up. In this scenario, the major advantage of Python is that it's a general-purpose language and gives you a lot of flexibility in data structures. Python is an excellent tool for more specialized analysis tasks, and is powered with related libraries to process data streams, to visualize datasets, and to carry out scientific calculations. Using Python for business intelligence (BI) can help you solve tricky problems in one go.

Rather than spending day after day scouring Internet forums for “how-to” information, here you'll find more than 60 recipes that take you through the entire process of creating actionable intelligence from your raw data, no matter what shape or form it's in. Within the first 30 minutes of opening this book, you'll learn how to use the latest in Python and NoSQL databases to glean insights from data just waiting to be exploited.

Real-Time Crypto

Learn how to use Bitcoin data to train an algorithm to execute crypto trades in real-time. Gain insight into blockchain and big data architectures. Walk away with the know how to build a quantitative trading pipeline on your own.

Have you ever wondered how to build a cryptocurrency trading bot? Have you wondered how to apply machine learning to the financial markets? Have you ever wondered how to get out of Excel and into the world of big data? You have come to the right place! Welcome to Real-Time Crypto. In this book we will build on your basic Python and data skills and turn you into a bona fide big data engineer. Along the way you will learn how to trade cryptocurrency in real-time, using cutting edge big data technology and machine learning.