machine learning systems designs that scale

Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems

Handbook of Data Intensive Computing

Data-intensive Systems: Principles and Fundamentals using Hadoop and Spark

Distributed Data Applications With Asp.Net

Data-Intensive Systems Quickstart: The Practical Basics of Storage, Streams, and Scaling (Concept Maps + Diagrams + Design Checklists)

Data-Intensive Computing: Architectures, Algorithms, and Applications

Designing Data-Intensive Applications, 2nd Edition: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems

Scaling Machine Learning with Spark

Scalable and Distributed Machine Learning and Deep Learning Patterns

Spark: The Definitive Guide: Big Data Processing Made Simple

Designing Big Data Platforms How to Use, Deploy, and Maintain Big Data Systems

Real-Time Data Processing: Harnessing the Power of Streaming Data

Scalable Big Data Architecture

Reliable Distributed Computing with the Isis Toolkit

Big Data Glossary: A Guide to the New Generation of Data Tools

Machine Learning Using R

High-Performance Big Data Computing

Transactions on Large-Scale Data- and Knowledge-Centered Systems XXIX

Big Data Computing: A Guide for Business and Technology Managers

28th International Conference on Distributed Computing Systems Workshops (Icdcs Workshops 2008)

2008 28th IEEE International Conference on Distributed Computing Systems - Icdcs 2008

Modern Technologies for Big Data Classification and Clustering

Modern Technologies for Big Data Classification and Clustering

Modern Technologies for Big Data Classification and Clustering

The Human Element of Big Data: Issues, Analytics, and Performance

Scaling up Machine Learning: Parallel and Distributed Approaches

Transactions on Large-Scale Data- and Knowledge-Centered Systems XV: Selected Papers from ADBIS 2013 Satellite Events

Data Management, Analytics and Innovation: Proceedings of ICDMAI 2025, Volume 3

Machine Learning Infrastructure and Best Practices for Software Engineers - by Miroslaw Staron (Paperback)

Designing Data-Intensive Applications by Martin Kleppmann Software Architecture & Distributed Systems Book Brand New

Building Machine Learning Systems With a Feature Store : Batch, Real-time, and Llm Systems

Data Analytics with Hadoop: An Introduction for Data Scientists

2007 Third International Workshop on Software Engineering for High Performance Computing Applications (Se-hpc)