Found inside – Page iThis book teaches you to do predictive, descriptive, and prescriptive analyses with Microsoft Power BI, Azure Data Lake, SQL Server, Stream Analytics, Azure Databricks, HD Insight, and more. Found insideThis book will help you improve your knowledge of building ML models using Azure and end-to-end ML pipelines on the cloud. About the book Spark in Action, Second Edition, teaches you to create end-to-end analytics applications. Gain expertise in processing and storing data by using advanced techniques with Apache SparkAbout This Book- Explore the integration of Apache Spark with third party applications such as H20, Databricks and Titan- Evaluate how Cassandra and ... Found inside – Page 216Best Practices for Scaling and Optimizing Apache Spark Holden Karau, Rachel Warren ... The spark-perf package, from Databricks, is designed for comparing ... Specifically, this book explains how to perform simple and complex data analytics and employ machine learning algorithms. Found inside – Page 1But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? Found insideAdvanced analytics on your Big Data with latest Apache Spark 2.x About This Book An advanced guide with a combination of instructions and practical examples to extend the most up-to date Spark functionalities. How will your organization be affected by these changes? This book, based on real-world cloud experiences by enterprise IT teams, seeks to provide the answers to these questions. This book also explains the role of Spark in developing scalable machine learning and analytics applications with Cloud technologies. Beginning Apache Spark 2 gives you an introduction to Apache Spark and shows you how to work with it. Build data-intensive applications locally and deploy at scale using the combined powers of Python and Spark 2.0 About This Book Learn why and how you can efficiently use Python to process data and build machine learning models in Apache ... Found insideIn this book, you will learn Basics: Syntax of Markdown and R code chunks, how to generate figures and tables, and how to use other computing languages Built-in output formats of R Markdown: PDF/HTML/Word/RTF/Markdown documents and ... This book will help object-oriented programmers build on their existing skills, allowing them to immediately construct useful applications as they gradually master advanced programming techniques. Found insideIt’s important to know how to administer SQL Database to fully benefit from all of the features and functionality that it provides. This book addresses important aspects of an Azure SQL Database instance such . Specifically, this book explains how to perform simple and complex data analytics and employ machine learning algorithms. Found insideDatabricks Contributes MLflow Machine Learning Platform to The Linux Foundation ... best practices for ML engineering into a standard platform that is open, ... Found insideThis book covers: Factors to consider when using Hadoop to store and model data Best practices for moving data in and out of the system Data processing frameworks, including MapReduce, Spark, and Hive Common Hadoop processing patterns, such ... The book also introduces a set of red flags that identify design problems. You can apply the ideas in this book to minimize the complexity of large software systems, so that you can write software more quickly and cheaply."-- Found inside – Page iThis book explains how the confluence of these pivotal technologies gives you enormous power, and cheaply, when it comes to huge datasets. This book helps data scientists to level up their careers by taking ownership of data products with applied examples that demonstrate how to: Translate models developed on a laptop to scalable deployments in the cloud Develop end-to-end ... Found insideWith this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas ... Found insideThis practical guide presents a collection of repeatable, generic patterns to help make the development of reliable distributed systems far more approachable and efficient. Found inside – Page 230... we will discuss the necessary libraries needed to perform the operations introduced, as well as providing some context on how best practices and some ... Found inside – Page 10MLflow was developed by Databricks as an open source machine learning ... we've chosen case studies with very different data and best practices. Found insideThis book will be your one-stop solution. Who This Book Is For This guide appeals to big data engineers, analysts, architects, software engineers, even technical managers who need to perform efficient data processing on Hadoop at real time. This book will help you master your skills in various artificial intelligence and machine learning services available on AWS. This book teaches you the different techniques using which deep learning solutions can be implemented at scale, on Apache Spark. This will help you gain experience of implementing your deep learning models in many real-world use cases. Found insideWith this practical guide, developers familiar with Apache Spark will learn how to put this in-memory framework to use for streaming data. Found inside – Page 175... 30 best practices, 5-9 code-free machine learning, 151-173 development environments, ... 76, 93, 95 Azure Container Services (ACI), 95 Azure Databricks ... Found insideEven those who know how to create ML models may be limited in how much they can explore. Once you complete this book, you’ll understand how to apply AutoML to your data right away. Found inside – Page 6For example, we can use Azure Databricks, Azure Machine Learning (AML), ... dealing with production systems, we'll focus a lot on DevOps and best practices. Found inside – Page 1This text's extensive set of web and network problems draw on rich public-domain data sources; many are accompanied by solutions in Python and/or R. Marketing Data Science will be an invaluable resource for all students, faculty, and ... Found insideDesign, implement, and deliver successful streaming applications, machine learning pipelines and graph applications using Spark SQL API About This Book Learn about the design and implementation of streaming applications, machine learning ... Found insideYour Python code may run correctly, but you need it to run faster. Updated for Python 3, this expanded edition shows you how to locate performance bottlenecks and significantly speed up your code in high-data-volume programs. The aim of this book is to make developers aware of best practices of Rust. In this book, you'll get to know all the best approaches a developer should follow and rules that should keep in mind at the time of development. Found insideThe book discusses how to build the data warehouse incrementally using the agile Data Vault 2.0 methodology. Found insideThe definitive guide for statisticians and data scientists who understand the advantages of becoming proficient in both R and Python The first book of its kind, Python for R Users: A Data Science Approach makes it easy for R programmers to ... Found insideLearn how to use, deploy, and maintain Apache Spark with this comprehensive guide, written by the creators of the open-source cluster-computing framework. Found inside – Page iSnowflake was built specifically for the cloud and it is a true game changer for the analytics market. This book will help onboard you to Snowflake, present best practices to deploy, and use the Snowflake data warehouse. Found insideThe updated edition of this practical book shows developers and ops personnel how Kubernetes and container technology can help you achieve new levels of velocity, agility, reliability, and efficiency. Found insideIn this book, you will learn how to: Develop a customer-centric strategy for your organization Understand the right way to think about customer lifetime value (CLV) Finetune investments in customer acquisition, retention, and development ... In this practical book, four Cloudera data scientists present a set of self-contained patterns for performing large-scale data analysis with Spark. Presents case studies and instructions on how to solve data analysis problems using Python. The Hitchhiker's Guide to Python takes the journeyman Pythonista to true expertise. This book covers relevant data science topics, cluster computing, and issues that should interest even the most advanced users. Found inside – Page iiSo reading this book and absorbing its principles will provide a boost—possibly a big boost—to your career. Found insideThis edition includes new information on Spark SQL, Spark Streaming, setup, and Maven coordinates. 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