Data Modeling & Design 2

Despite the excitement around "data science," "big data," and "analytics," the ambiguity of these terms has led to poor communication between data scientists and organizations seeking their help. In……続きを見る

Deep learning networks are getting smaller. Much smaller. The Google Assistant team can detect words with a model just 14 kilobytes in sizeーsmall enough to run on a microcontroller. With this pract……続きを見る

Work with data like a pro using this guide that breaks down how to organize, apply, and most importantly, understand what you are analyzing in order to become a true data ninja. From the stock marke……続きを見る

As data management continues to evolve rapidly, managing all of your data in a central place, such as a data warehouse, is no longer scalable. Today's world is about quickly turning data into value.……続きを見る

With the explosion of data, computing power, and cloud data warehouses, SQL has become an even more indispensable tool for the savvy analyst or data scientist. This practical book reveals new and hi……続きを見る

Build a solid foundation in algorithmic trading by developing, testing and executing powerful trading strategies with real market data using Python Key Features Build a strong foundation in algorit……続きを見る

As data floods into your company, you need to put it to work right awayーand SQL is the best tool for the job. With the latest edition of this introductory guide, author Alan Beaulieu helps develope……続きを見る

The financial industry has recently adopted Python at a tremendous rate, with some of the largest investment banks and hedge funds using it to build core trading and risk management systems. Updated……続きを見る

A guide for using computational text analysis to learn about the social world From social media posts and text messages to digital government documents and archives, researchers are bombarded with a……続きを見る

Give your organization the data protection it deserves without the uncertainty and cost overruns experienced by your predecessors or other companies. System and network administrators have their wor……続きを見る

Get command of your organizational Big Data using the power of data science and analytics About This Book • A perfect companion to boost your Big Data storing, processing, analyzing skills to help y……続きを見る

Get up to speed with using Mermaid diagrams to facilitate a seamless development workflow with the help of real-world examples and expert tips from the creators of the tool Key Features • Learn how ……続きを見る

The low cost of getting started with cloud services can easily evolve into a significant expense down the road. That's challenging for teams developing data pipelines, particularly when rapid change……続きを見る

Use modern Python libraries such as pandas, NumPy, and scikit-learn and popular machine learning and deep learning methods to solve financial modeling problems Purchase of the print or Kindle book i……続きを見る

How many buyers will an additional dollar of online marketing bring in? Which customers will only buy when given a discount coupon? How do you establish an optimal pricing strategy? The best way to ……続きを見る

For self-service data preparation, Tableau Prep is relatively easy to useーas long as you know how to clean and organize your datasets. Carl Allchin, from The Information Lab in London, gets you up ……続きを見る

Process tabular data and build high-performance query engines on modern CPUs and GPUs using Apache Arrow, a standardized language-independent memory format, for optimal performanceKey FeaturesLearn ……続きを見る

Python is a first-class tool for many researchers, primarily because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this ……続きを見る

Data is a fantastic raw resource for powering change in an organization, but all too often the people working in those organizations don't have the necessary skills to communicate with data effectiv……続きを見る

What value does semantic data modeling offer? As an information architect or data science professional, let’s say you have an abundance of the right data and the technology to extract business gold……続きを見る

What is bad data? Some people consider it a technical phenomenon, like missing values or malformed records, but bad data includes a lot more. In this handbook, data expert Q. Ethan McCallum has gath……続きを見る

Success in data science depends on the flexible and appropriate use of tools. That includes Python and R, two of the foundational programming languages in the field. This book guides data scientists……続きを見る

Perform time series analysis and forecasting confidently with this Python code bank and reference manual Key Features • Explore forecasting and anomaly detection techniques using statistical, machin……続きを見る

Nowadays, finance, mathematics, and programming are intrinsically linked. This book provides the relevant foundations of each discipline to give you the major tools you need to get started in the wo……続きを見る

Data Science for Business with R, written by Jeffrey S. Saltz and Jeffrey M. Stanton,focuses on the concepts foundational for students starting a business analytics or data science degree program. T……続きを見る

Effective visualization is the best way to communicate information from the increasingly large and complex datasets in the natural and social sciences. But with the increasing power of visualization……続きを見る

Gain hands-on experience with SPARQL, the RDF query language that’s bringing new possibilities to semantic web, linked data, and big data projects. This updated and expanded edition shows you how to……続きを見る

Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice. With this practical book, you……続きを見る

Data is getting bigger and more complex by the day, and so are your choices in handling it. Explore some of the most cutting-edge databases available - from a traditional relational database to newe……続きを見る

Data pipelines are the foundation for success in data analytics. Moving data from numerous diverse sources and transforming it to provide context is the difference between having data and actually g……続きを見る