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Data science — Сторінка 49
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Understanding Enterprise SOA, Eric Pulier, Hugh Taylor
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Type-Driven Development with Idris, Edwin Brady
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Rails 4 in Action: Revised Edition of Rails 3 in Action 2nd Edition, Ryan Bigg, Yehuda Katz, Steve Klabnik,
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React in Action, Mark Tielens Thomas
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Adobe AIR in Action, Joseph Lott, Kathryn Rotondo, Samuel Ahn, Ashley Atkins, Max Jackson, more
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PowerShell Deep Dives, Jeffery Hicks, Richard Siddaway, Oisin Grehan, Aleksandar Nikolic, more
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Griffon In Action, Danno Ferrin James Shingler Andres Almiray
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The Ai Organization: Learn from Real Companies and Microsofts Journey How to Redefine Your Organization With
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Kotlin Cookbook: A Problem-Focused Approach, Ken Kousen
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Implementing MLOps in the Enterprise: A Production-First Approach, Yaron Haviv, Noah Gift
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Quarkus Cookbook: Kubernetes-Optimized Java Solutions, Alex Bueno, Jason Porter
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Hands-On Healthcare Data: Taming the Complexity of Real-World Data, Andrew Nguyen
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The Self-Service Data Roadmap: Democratize Data and Reduce Time to Insight, Sandeep Uttamchandani
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97 Things Every Scrum Practitioner Should Know: Collective Wisdom from the Experts, Gunther Verheyen
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Blueprints for Text Analytics Using Python: Machine Learning-Based Solutions for Common Real World (NLP)
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97 Things Every Engineering Manager Should Know: Collective Wisdom from the Experts, Camille Fournier
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AI for People and Business: A Framework for Better Human Experiences and Business Success, Alex Castrounis
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Product Research Rules: Nine Foundational Rules for Product Teams to Run Accurate Research that Delivers
649
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Automating Data Quality Monitoring: Scaling Beyond Rules with Machine Learning, Jeremy Stanley, Paige Schwartz
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Collaborative Product Design: Help Any Team Build a Better Experience, Austin Govella
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Programming C# 10: Build Cloud, Web, and Desktop Applications, Ian Griffiths
999
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Learning GraphQL: Declarative Data Fetching for Modern Web Apps, Eve Porcello, Alex Banks
549
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Genomics in the Azure Cloud: Scaling Your Bioinformatics Workloads Using Enterprise-Grade Solutions, Colby
699
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97 Things Every Cloud Engineer Should Know: Collective Wisdom from the Experts, Emily Freeman, Nathen Harvey
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Building Machine Learning Pipelines: Automating Model Life Cycles with TensorFlow, Hannes Hapke, Catherine
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Data Curious: Applying Agile Analytics for Better Business Decisions, Carl Allchin, Sarah Nabelsi
599
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Cost-Effective Data Pipelines: Balancing Trade-Offs When Developing Pipelines in the Cloud, Sev Leonard
649
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5
Mastering Financial Pattern Recognition: Finding and Back-Testing Candlestick Patterns with Python, Sofien
649
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Learning Dapr: Building Distributed Cloud Native Applications, Haishi Bai, Yaron Schneider
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Essential Math for AI: Next-Level Mathematics for Efficient and Successful AI Systems, Hala Nelson
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5
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