机读格式显示(MARC)
- 000 04509cam a2200445 i 4500
- 008 190227s2019 caua f ab 000 0 eng d
- 020 __ |a 9781681734989 |c CNY602.01
- 040 __ |a CaBNVSL |b eng |e rda |c CaBNVSL |d MiU
- 100 1_ |a Boehm, Matthias, |e author.
- 245 10 |a Data management in machine learning systems / |c Matthias Boehm, Arun Kumar, Jun Yang.
- 260 __ |a [San Rafael, California] : |b Morgan and Claypool, |c 2019.
- 300 __ |a xv, 157 pages : |b illustrations ; |c 24 cm.
- 336 __ |a text |2 rdacontent
- 337 __ |a electronic |2 isbdmedia
- 338 __ |a volume |2 rdacarrier
- 490 0_ |a Synthesis lectures on data management, |x 2153-5426 ; |v # 57
- 500 __ |a Part of: Synthesis digital library of engineering and computer science.
- 504 __ |a Includes bibliographical references (pages 127-156)
- 505 0_ |a 1. Introduction -- 1.1 Overview of ML lifecycle and ML users -- 1.2 Motivation -- 1.3 Outline and scope --
- 505 8_ |a 2. ML through database queries and UDFs -- 2.1 Linear algebra -- 2.2 Iterative algorithms -- 2.3 Sampling-based methods -- 2.4 Discussion -- 2.5 Summary --
- 505 8_ |a 3. Multi-table ML and deep systems integration -- 3.1 Learning over joins -- 3.2 Statistical relational learning and non-IID models -- 3.3 Deeper integration and specialized DBMSs -- 3.4 Summary --
- 505 8_ |a 4. Rewrites and optimization -- 4.1 Optimization scope -- 4.2 Logical rewrites and planning -- 4.3 Physical rewrites and operators -- 4.4 Automatic operator fusion -- 4.5 Runtime adaptation -- 4.6 Summary --
- 505 8_ |a 5. Execution strategies -- 5.1 Data-parallel execution -- 5.2 Task-parallel execution -- 5.3 Parameter servers (model-parallel execution) -- 5.4 Hybrid execution strategies -- 5.5 Accelerators (GPUs, FPGAs, ASICs) -- 5.6 Summary --
- 505 8_ |a 6. Data access methods -- 6.1 Caching and buffer pool management -- 6.2 Compression -- 6.3 NUMA-aware partitioning and replication -- 6.4 Index structures -- 6.5 Summary --
- 505 8_ |a 7. Resource heterogeneity and elasticity -- 7.1 Provisioning, configuration, and scheduling -- 7.2 Handling failures -- 7.3 Working with markets of transient resources -- 7.4 Summary --
- 505 8_ |a 8. Systems for ML lifecycle tasks -- 8.1 Data sourcing and cleaning for ML -- 8.2 Feature engineering and deep learning -- 8.3 Model selection and model management -- 8.4 Interaction, visualization, debugging, and inspection -- 8.5 Model deployment and serving -- 8.6 Benchmarking ML systems -- 8.7 Summary --
- 505 8_ |a 9. Conclusions -- Bibliography -- Authors' biographies.
- 520 __ |a Large-scale data analytics using machine learning (ML) underpins many modern data-driven applications. ML systems provide means of specifying and executing these ML workloads in an efficient and scalable manner. Data management is at the heart of many ML systems due to data-driven application characteristics, data-centric workload characteristics, and system architectures inspired by classical data management techniques. In this book, we follow this data-centric view of ML systems and aim to provide a comprehensive overview of data management in ML systems for the end-to-end data science or ML lifecycle. We review multiple interconnected lines of work: (1) ML support in database (DB) systems, (2) DB-inspired ML systems, and (3) ML lifecycle systems. Covered topics include: in-database analytics via query generation and user-defined functions, factorized and statistical-relational learning; optimizing compilers for ML workloads; execution strategies and hardware accelerators; data access methods such as compression, partitioning and indexing; resource elasticity and cloud markets; as well as systems for data preparation for ML, model selection, model management, model debugging, and model serving. Given the rapidly evolving field, we strive for a balance between an up-to-date survey of ML systems, an overview of the underlying concepts and techniques, as well as pointers to open research questions. Hence, this book might serve as a starting point for both systems researchers and developers.
- 650 _0 |a Database management.
- 650 _0 |a Machine learning.
- 700 1_ |a Kumar, Arun, |e author.
- 700 1_ |a Yang, Jun, |d 1975 September 9- |e author.
- 730 0_ |a Synthesis digital library of engineering and computer science.