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How to configure Grafana as code | Grafana Labs
Solutions All end-to-end solutions Opinionated solutions that help you get there easier and faster
GitHub - anhaidgroup/deepmatcher: Python package for performing Entity and Text Matching using Deep Learning.
DeepMatcher is a Python package for performing entity and text matching using deep learning. It provides built-in neural networks and utilities that enable you to train and apply state-of-the-art deep learning models for entity matching in less than 10 lines of code. The models are also easily customizable - the modular design allows any subcomponent to be altered or swapped out for a custom imple
Database Systems: The Complete Book
Welcome to the home page for Database Systems: The Complete Book (DS:CB), by Hector Garcia-Molina, Jeff Ullman, and Jennifer Widom. The second edition of this book was published on June 9, 2008. Some material on this page is also relevant to A First Course in Database Systems, 3nd Edition. The Gradiance contract with Pearson (Addison-Wesley + Prentice-Hall) has terminated, and we have decided to t
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Foundations of Databases
You may take one copy of the book draft for personal use but not for distribution. Please do not post the draft on other web sites, instead, please put a link to this site. Alice's book Individual Chapters Table of Contents Chapter 1 - Database Systems Chapter 2 - Theoretical Background Chapter 3 - The Relational Model Chapter 4 - Conjunctive Queries Chapter 5 - Adding Negation: Algebra and Calcul
世界ã®å°å£²æ¥ãƒ©ãƒ³ã‚ング2023｜コンシューマービジãƒã‚¹ï½œDeloitte Japan
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Wavefront as code using Terraform Integration — Part III
Terraform Registry
http://www.vldb.org/pvldb/vol11/p2042-govind.pdf
CS520: Knowledge Graph Seminar Session 4 (Spring 2020)
https://dl.acm.org/doi/10.1145/3318464.3380605
Data Market Platforms: Trading Data Assets to Solve Data Problems
https://dl.acm.org/doi/10.1145/3318464.3389726
Principles of scalable data management (CS7240), Spring 2020
Lecture Slides for Algorithm Design by Jon Kleinberg And Éva Tardos
MIT Visualization Group
What I Learned at SIGMOD 2020
SIGMOD 2020 conference experience
Arvind Satyanarayan
HILDA 2020: Workshop on Human-In-the-Loop Data Analytics
Industry-Scale Knowledge Graphs – Communications of the ACM
Panel: Enterprise-Scale Knowledge Graphs « ISWC 2018
Aurum: Discovering Data in Lakes, Clouds and Databases
A Primer on Provenance - ACM Queue
Home - HOMEX Services Group
Talks and Ramblings by Anant Narayanan
Enterprise Scale Knowledge Graphs
Graph algorithms - Neo4j Graph Data Science
GitHub - RJMillerLab/data-lake-tutorial-slides: Data Lake Management: Challenges and Opportunities, VLDB 2019
https://people.csail.mit.edu/meyer/mcs.pdf
DATA Lab @ Northeastern – Scalable Management and Analysis of Big Data
Renée Miller - Khoury College of Computer Sciences
https://www.juansequeda.com/blog/2020/06/22/sigmod-2020-a-virtual-trip-report/
Human-Centered Study of Data Science Work Practices
The 80/20 data science dilemma
Introducing Observable, Self-Documenting ELT
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