About data-driven attribution - Google Ads Help
Data-driven attribution is the default attribution model for most conversion actions. Follow the instructions below to update an existing conversion action's attribution model to "Data-driven": In …
"Enroll in Best Data Analyst Course by SLA Consultants India" Cloud & Big Da…
As organizations continue to shift their operations to the cloud, the demand for professionals skilled in cloud and big data analytics is growing rapidly. In 2026, companies will rely heavily on cloud...
3 Easy Ways to Back up Your Important Data and Keep it Secure
If you have important data on your work phone and want to make sure you don't lose it, you can use HONOR Device Clone to back it up to another phone. Turn on Device Clone, and the basic data can …
Evaluating the Impact Of Spatial Features Of Mobility Data and Index Choice On D…
The growing number of moving Internet-of-Things (IoT) devices has led to a surge in moving object data, powering applications such as traffic routing, hotspot detection, or weather forecasting. When managing such data, spatial database systems offer...
Investigating the Ways in Which Mobile Phone Images with Open-Source Data Can Be…
This paper presents the development of an interactive system for constructing Augmented Virtual Environments (AVEs) by fusing mobile phone images with open-source geospatial data. By integrating 2D image data with 3D models derived from sources such...
Decomposition of quantitative Gaifman graphs as a data analysis tool
We argue the usefulness of Gaifman graphs of first-order relational structures as an exploratory data analysis tool. We illustrate our approach with cases where the modular decompositions of these graphs reveal interesting facts about the data. Then,...
scribe-org/Scribe-Data
Wikidata and Wiktionary language data extraction (⭐ 52)
Leveraging Mobile Phone Data for Migration Flows
Statistics on migration flows are often derived from census data, which suffer from intrinsic limitations, including costs and infrequent sampling. When censuses are used, there is typically a time gap - up to a few years - between the data collectio...
Price Optimization Combining Conjoint Data and Purchase History: A Causal Modeli…
Pricing decisions of companies require an understanding of the causal effect of a price change on the demand. When real-life pricing experiments are infeasible, data-driven decision-making must be based on alternative data sources such as purchase hi...
Understand RTB breakout data - Authorized Buyers Help
Understand RTB breakout data Learn the best methods for increasing impression availability with RTB Breakout The real-time bidding activity data shown in RTB breakout displays bid responses and …
haozhang-x/spring-boot-data-desensitize
Jackson Data Desensitize（Spring Boot 数据脱敏） (⭐ 22)
Estimation of Residential Radon Concentration in Pennsylvania Counties by Data F…
A data fusion method for the estimation of residential radon level distribution in any Pennsylvania county is proposed. The method is based on a multi-sample density ratio model with variable tilts and is applied to combined radon data from a referen...
Combining astrophysical datasets with CRUMB
At present, the field of astronomical machine learning lacks widely-used benchmarking datasets; most research employs custom-made datasets which are often not publicly released, making comparisons between models difficult. In this paper we present CR...
DeepXiv-SDK: An Agentic Data Interface for Scientific Literature
LLM-agents are increasingly used to accelerate the progress of scientific research. Yet a persistent bottleneck is data access: agents not only lack readily available tools for retrieval, but also have to work with unstrcutured, human-centric data on...
davidsbatista/Annotated-Semantic-Relationships-Datasets
A collections of public and free annotated datasets of relationships between entities/nominals (Portuguese and English) (⭐ 703)
Data as a service - Wikipedia
value propositions and customers: Answers as a Service; Information as a Service; Data as a Service. Data as a Service vendors use different types of
evenlode10/Python-Programming-for-Data-Science-Part-1
This is the repository for Python Programming for Data Science Part 1, authored by Massimiliano Izzo (⭐ 0)
Distilling Datasets Into Less Than One Image
Dataset distillation aims to compress a dataset into a much smaller one so that a model trained on the distilled dataset achieves high accuracy. Current methods frame this as maximizing the distilled classification accuracy for a budget of K distille...
Dataset Distillation via Curriculum Data Synthesis in Large Data Era
Dataset distillation or condensation aims to generate a smaller but representative subset from a large dataset, which allows a model to be trained more efficiently, meanwhile evaluating on the original testing data distribution to achieve decent perf...
UDO: Universal Database Optimization using Reinforcement Learning
UDO is a versatile tool for offline tuning of database systems for specific workloads. UDO can consider a variety of tuning choices, reaching from picking transaction code variants over index selections up to database system parameter tuning. UDO use...