iPhoneAlle anzeigen
iPhone 11iPhone 11 ProiPhone 11 Pro MaxiPhone 12iPhone 12 ProiPhone 12 Pro MaxiPhone 12 miniiPhone 13iPhone 13 ProiPhone 13 Pro MaxiPhone 13 miniiPhone 14iPhone 14 PlusiPhone 14 ProiPhone 14 Pro MaxiPhone 15iPhone 15 PlusiPhone 15 ProiPhone 15 Pro MaxiPhone 16iPhone 16 PlusiPhone 16 ProiPhone 16 Pro MaxiPhone 16eiPhone 8iPhone 8 PlusiPhone SE 2020iPhone SE 2022iPhone XiPhone XRiPhone XSiPhone XS Max
Galaxy A-SerieAlle anzeigen
Galaxy A12Galaxy A13Galaxy A13 5GGalaxy A14Galaxy A15Galaxy A16Galaxy A17Galaxy A17 5GGalaxy A20eGalaxy A21Galaxy A22Galaxy A23Galaxy A24Galaxy A25Galaxy A26 5GGalaxy A32Galaxy A33Galaxy A34Galaxy A35Galaxy A36 5GGalaxy A37Galaxy A40Galaxy A41Galaxy A42Galaxy A50Galaxy A51Galaxy A52Galaxy A53Galaxy A54Galaxy A55Galaxy A56 5GGalaxy A57 5GGalaxy A70Galaxy A71Galaxy A72
Redmi SeriesAlle anzeigen
Redmi 10Redmi 13CRedmi 15 5GRedmi Note 10Redmi Note 10 ProRedmi Note 11Redmi Note 11 ProRedmi Note 11 Pro Plus 5GRedmi Note 11sRedmi Note 12Redmi Note 12 5GRedmi Note 12 ProRedmi Note 12 Pro 5GRedmi Note 12 Pro PlusRedmi Note 13Redmi Note 13 5GRedmi Note 13 ProRedmi Note 13 Pro PlusRedmi Note 14Redmi Note 14 Pro PlusRedmi Note 15Redmi Note 15 5GRedmi Note 15 ProRedmi Note 15 Pro 5GRedmi Note 15 Pro Plus 5GRedmi Note 8Redmi Note 8 ProRedmi Note 9Redmi Note 9 Pro
Handgeprüfte Gebrauchtware
Bis zu 50 % günstiger als neu
Der Umwelt zuliebe
Optischer Zustand
Beschreibung
Gain a practical introduction to DataOps, a new discipline for delivering data science at scale inspired by practices at companies such as Facebook, Uber, LinkedIn, Twitter, and eBay. Organizations need more than the latest AI algorithms, hottest tools, and best people to turn data into insight-driven action and useful analytical data products. Processes and thinking employed to manage and use… data in the 20th century are a bottleneck for working effectively with the variety of data and advanced analytical use cases that organizations have today. This book provides the approach and methods to ensure continuous rapid use of data to create analytical data products and steer decision making. Practical DataOps shows you how to optimize the data supply chain from diverse raw data sources to the final data product, whether the goal is a machine learning model or other data-orientated output. The book provides an approach to eliminate wasted effort and improve collaboration between data producers, data consumers, and the rest of the organization through the adoption of lean thinking and agile software development principles. This book helps you to improve the speed and accuracy of analytical application development through data management and DevOps practices that securely expand data access, and rapidly increase the number of reproducible data products through automation, testing, and integration. The book also shows how to collect feedback and monitor performance to manage and continuously improve your processes and output. What You Will Learn Develop a data strategy for your organization to help it reach its long-term goals Recognize and eliminate barriers to delivering data to users at scale Work on the right things for the right stakeholders through agile collaboration Create trust in data via rigorous testing and effective data management Build a culture of learning and continuous improvement through monitoring deployments and measuring outcomes Create cross-functional self-organizing teams focused on goals not reporting lines Build robust, trustworthy, data pipelines in support of AI, machine learning, and other analytical data products Who This Book Is For Data science and advanced analytics experts, CIOs, CDOs (chief data officers), chief analytics officers, business analysts, business team leaders, and IT professionals (data engineers, developers, architects, and DBAs) supporting data teams who want to dramatically increase the value their organization derives from data. The book is ideal for data professionals who want to overcome challenges of long delivery time, poor data quality, high maintenance costs, and scaling difficulties in getting data science output and machine learning into customer-facing production. 48,14 €
Taschenbuch | Neu
oder
zzgl.
Du kannst wie immer einen Kaufalarm setzen, wenn du auf das gebrauchte Buch warten möchtest.
zzgl.
Handgeprüfte Gebrauchtware
Bis zu 50 % günstiger als neu
Der Umwelt zuliebe
Technische Daten
Erscheinungsdatum
10.12.2019
Sprache
Englisch
Originalsprache
Englisch
EAN
9781484251034
Herausgeber
APRESS
Sonderedition
Nein
Autor
Harvinder Atwal
Seitenanzahl
275
Auflage
1st edition
Einbandart
Taschenbuch
Transparenz & Sicherheit
Hersteller: Apress, Europaplatz 3, Heidelberg, Deutschland, 69115, ProductSafety@springernature.com, Springer Nature Customer Service Center GmbH
-.-
★★★★★
☆☆☆☆☆ Leider noch keine Bewertungen
Leider noch keine Bewertungen
Sicher bei rebuy kaufen
Schreib die erste Bewertung für dieses Produkt!
Wenn du eine Bewertung für dieses Produkt schreibst, hilfst du allen Kund:innen, die noch überlegen, ob sie das Produkt kaufen wollen. Vielen Dank, dass du mitmachst!
Sicher bei rebuy kaufen