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Machine Learning Engineering in Action lays out an approach to building deployable, maintainable production machine learning systems. You will adopt software development standards …
"To me, this has always been the defacto standard for documentation on the Spring Framework. I bought the 1st edition when it first came out as we were converting alegacy app to …
To lead a data science team, you need to expertly articulate technology roadmaps, support a data-driven culture, and plan a data strategy that drives a competitive business plan. …
Running your systems in the cloud doesn't automatically make them secure. To create secure applications and infrastructure on AWS, you need to understand the tools and features the …
Kafka in Action is a practical, hands-on guide to building Kafka-based data pipelines. Filled with real-world use cases and scenarios, this book probes Kafka's most common use …
An effective DBA is an efficient DBA. And if you work with SQL Server, dbatools is a lifesaver. With over 500 commands, this free and open source PowerShell module has the …
In Algorithms and Data Structures for Massive Datasets, you'll discover methods for reducing and sketching data so it fits in small memory without losing accuracy, and unlock the …
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 …
Spring Boot in Practice covers dozens of handy Spring Boot development techniques, from basic functions to hidden features you probably didn't even know existed. Each recipe is …
When it comes to data analytics, it pays tothink big. PySpark blends the powerful Spark big data processing engine withthe Python programming language to provide a data analysis …