Data Analytics

The past two decades have seen an explosion both in the volume of data we use, and our understanding of its management.However, while techniques and technology for manipulating data have advanced rapidly in this time, the concepts around the value of our...

With the resurgence of neural networks in the 2010s, deep learning has become essential for machine learning practitioners and even many software engineers. This book provides a comprehensive introduction for data scientists and software engineers with...

Become a successful data engineer by building and deploying your own data pipelines on Google Cloud, including making key architectural decisions Key Features Get up to speed with data governance on Google Cloud Learn how to use various Google...

Add Data and Analytics to Your TD ToolkitInstructional design pro Megan Torrance addresses the importance of instructional designers accessing and applying learning and performance data-from how to design learning experiences with data collection in mind...

Since the first edition of this book published, Bayesian networks have become even more important for applications in a vast array of fields. This second edition includes new material on influence diagrams, learning from data, value of information,...

Mikhail Zhilkin, a data scientist who has worked on projects ranging from Candy Crush games to Premier League football players' physical performance, shares his strong views on some of the best and, more importantly, worst practices in data analytics and...

Get the lowdown on CockroachDB, the distributed SQL database built to handle the demands of today's data-driven cloud applications. In this hands-on guide, software developers, architects, and DevOps/SRE teams will learn how to use CockroachDB to create...

Data can be a cost for some organizations, but for those who succeed, it is a way to drive profitability, customer loyalty, and outperform others in their field. A well thought out, fit-for-purpose data strategy is vital for every modern data-driven...

The Contemporary Introduction to Deep Reinforcement Learning that Combines Theory and Practice Deep reinforcement learning (deep RL) combines deep learning and reinforcement learning, in which artificial agents learn to solve sequential decision-making...

Build predictive models from time-based patterns in your data. Master statistical models including new deep learning approaches for time series forecasting. In Time Series Forecasting in Python you will learn how to: Recognize a...

One of the key open questions within arti?cial intelligence is how to combine probability and logic with learning. This question is getting an increased - tentioninseveraldisciplinessuchasknowledgerepresentation,reasoningabout uncertainty, data mining,...

Create and improve fully automated forecasts for time series data with strong seasonal effects, holidays, and additional regressors using Python Purchase of the print or Kindle book includes a free PDF eBook Key Features Explore Prophet, the open...

Build powerful, production-ready search applications using the incredible features of Elasticsearch. In ElasticSearch in Action, Second Edition you will discover: Architecture, concepts, and fundamentals of ElasticsearchInstalling,...

Implement the Snowflake Data Cloud using best practices and reap the benefits of scalability and low-cost from the industry-leading, cloud-based, data warehousing platform. This book provides a detailed how-to explanation, and assumes familiarity with...

Built specifically for statistical computing and graphics, the R language, along with its amazing collection of libraries and tools, is one of the most powerful tools you can use to tackle data analysis for business, research, and other data-intensive...

The Digital Humanities Coursebook provides critical frameworks for the application of digital humanities tools and platforms, which have become an integral part of work across a wide range of disciplines. Written by an expert with twenty years of...

This book comprehensively covers the topic of recommender systems, which provide personalized recommendations of products or services to users based on their previous searches or purchases. Recommender system methods have been adapted to diverse...

Apache Spark is amazing when everything clicks. But if you haven't seen the performance improvements you expected, or still don't feel confident enough to use Spark in production, this practical book is for you. Authors Holden Karau and Rachel Warren...

Discover all the essential design and architectural patterns in one place to help you rapidly build and deploy your modern data platform using AWS services Key Features Learn to build modern data platforms on AWS using data lakes and purpose-built...

What happens when a researcher and a practitioner spend hours crammed in a Fiat discussing data visualization? Beyond creating beautiful charts, they found greater richness in the craft as an integrated whole. Drawing from their unconventional...

Demonstrate your Data Science skills by earning the brand-new CompTIA DataX credential In CompTIA DataX Study Guide: Exam DY0-001, data scientist and analytics professor, Fred Nwanganga, delivers a practical, hands-on guide to establishing your...

Master Data Analytics Hands-On by Solving Fascinating Problems You'll Actually Enjoy! Harvard Business Review recently called data science "The Sexiest Job of the 21st Century." It's not just sexy: For millions of managers, analysts, and students who...

There are many excellent R resources for visualization, data science, and package development. Hundreds of scattered vignettes, web pages, and forums explain how to use R in particular domains. But little has been written on how to simply make R work...

Design for large-scale, high-performance queries using Snowflake's query processing engine to empower data consumers with timely, comprehensive, and secure access to data. This book also helps you protect your most valuable data assets using built-in...

Detect fraud earlier to mitigate loss and prevent cascading damage Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques is an authoritative guidebook for setting up a comprehensive fraud detection analytics solution. Early...

"A First Course in Machine Learning by Simon Rogers and Mark Girolami is the best introductory book for ML currently available. It combines rigor and precision with accessibility, starts from a detailed explanation of the basic foundations of Bayesian...

Turning text into valuable information is essential for businesses looking to gain a competitive advantage. With recent improvements in natural language processing (NLP), users now have many options for solving complex challenges. But it's not always...

This book examines the growing importance of algorithms and automation-including emerging forms of artificial intelligence-in the gathering, composition, and distribution of news. In it the authors connect a long line of research on journalism and...

Leverage a lightning fast DataFrame library for efficient data wrangling in Python Key Features Unlock the power of Python Polars for faster and more efficient data analysis workflows Master the fundamentals of Python Polars with step-by-step...

This book provides a practical and fairly comprehensive review of Data Science through the lens of dimensionality reduction, as well as hands-on techniques to tackle problems with data collected in the real world. State-of-the-art results and solutions...

Get to know the 'why' and 'how' of machine learning and big data in quantitative investment Big Data and Machine Learning in Quantitative Investment is not just about demonstrating the maths or the coding. Instead, it's a book by practitioners for...

Learn how to perform data analysis with the R language and software environment, even if you have little or no programming experience. With the tutorials in this hands-on guide, you'll learn how to use the essential R tools you need to know to analyze...

Helping tech-savvy marketers and data analysts solve real-world business problems with Excel Using data-driven business analytics to understand customers and improve results is a great idea in theory, but in today's busy offices, marketers and analysts...

This book comprehensively covers the topic of recommender systems, which provide personalized recommendations of products or services to users based on their previous searches or purchases. Recommender system methods have been adapted to diverse...

Get up to speed on Apache Accumulo, the flexible, high-performance key/value store created by the National Security Agency (NSA) and based on Google's BigTable data storage system. Written by former NSA team members, this comprehensive tutorial and...

Feature engineering is a crucial step in the machine-learning pipeline, yet this topic is rarely examined on its own. With this practical book, you'll learn techniques for extracting and transforming features-the numeric representations of raw data-into...

Master business modeling and analysis techniques with Microsoft Excel 2016, and transform data into bottom-line results. Written by award-winning educator Wayne Winston, this hands on, scenario-focused guide helps you use Excel's newest tools to ask the...

Big Data Solution Architecture provides everyone from CIOs and COOs to lead architects and lead developers with the fundamental concepts of big data development. Authors Ted Malaska and Jonathan Seidman guide you through all the major components...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9780062390851Author Seth Stephens-DavidowitzFormat HardbackPage Count 352Imprint Dey Street BooksPublisher Dey Street BooksWeight(grams) 408g

The definitive, easy-to-follow guide to writing Python code with spatial data in ArcGIS Pro, whether you're new to programming or not. Python Scripting for ArcGIS Pro starts with the fundamentals of Python programming and then dives into how to write...