Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Non-Hispanic population of White Earth by race. It includes the distribution of the Non-Hispanic population of White Earth across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of White Earth across relevant racial categories.
Key observations
With a zero Hispanic population, White Earth is 100% Non-Hispanic. Among the Non-Hispanic population, the largest racial group is White alone with a population of 76 (100% of the total Non-Hispanic population).
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for White Earth Population by Race & Ethnicity. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the White Earth population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of White Earth across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.
Key observations
In 2023, the population of White Earth was 93, a 0% decrease year-by-year from 2022. Previously, in 2022, White Earth population was 93, a decline of 4.12% compared to a population of 97 in 2021. Over the last 20 plus years, between 2000 and 2023, population of White Earth increased by 28. In this period, the peak population was 99 in the year 2020. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).
When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).
Data Coverage:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for White Earth Population by Year. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the White Earth population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of White Earth. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.
Key observations
The largest age group was 18 to 64 years with a poulation of 42 (55.26% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
Age cohorts:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for White Earth Population by Age. You can refer the same here
As a source of animal and plant population data, the Global Population Dynamics Database (GPDD) is unrivalled. Nearly five thousand separate time series are available here. In addition to all the population counts, there are taxonomic details of over 1400 species. The type of data contained in the GPDD varies enormously, from annual counts of mammals or birds at individual sampling sites, to weekly counts of zooplankton and other marine fauna. The project commenced in October 1994, following discussions on ways in which the collaborating partners could make a practical and enduring contribution to research into population dynamics. A small team was assembled and, with assistance and advice from numerous interested parties we decided to construct the database using the popular Microsoft Access platform. After an initial design phase, the major task has been that of locating, extracting, entering and validating the data in all the various tables. Now, nearly 5000 individual datasets have been entered onto the GPDD. The Global Population Dynamics Database comprises six Tables of data and information. The tables are linked to each other as shown in the diagram shown in figure 3 of the GPDD User Guide (GPDD-User-Guide.pdf). Referential integrity is maintained through record ID numbers which are held, along with other information in the Main Table. It's structure obeys all the rules of a standard relational database.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of White Earth by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for White Earth. The dataset can be utilized to understand the population distribution of White Earth by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in White Earth. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for White Earth.
Key observations
Largest age group (population): Male # 10-14 years (17) | Female # 40-44 years (13). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
Age groups:
Scope of gender :
Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for White Earth Population by Gender. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the White Earth population by race and ethnicity. The dataset can be utilized to understand the racial distribution of White Earth.
The dataset will have the following datasets when applicable
Please note that in case when either of Hispanic or Non-Hispanic population doesnt exist, the respective dataset will not be available (as there will not be a population subset applicable for the same)
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
https://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement
Welcome to the Caucasian Human Facial Images Dataset, curated to advance facial recognition technology and support the development of secure biometric identity systems, KYC verification processes, and AI-driven computer vision applications. This dataset is designed to serve as a robust foundation for real-world face matching and recognition use cases.
The dataset contains over 1,000 facial image sets of Caucasian individuals. Each set includes:
All images were captured with real-world variability to enhance dataset robustness:
Each participant’s data is accompanied by rich metadata to support AI model training, including:
This metadata enables targeted filtering and training across diverse scenarios.
This dataset is ideal for a wide range of AI and biometric applications:
To meet evolving AI demands, this dataset is regularly updated and can be customized. Available options include:
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of White Earth by race. It includes the population of White Earth across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of White Earth across relevant racial categories.
Key observations
The percent distribution of White Earth population by race (across all racial categories recognized by the U.S. Census Bureau): 100% are white.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for White Earth Population by Race & Ethnicity. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual white student percentage from 1991 to 2023 for Rim Of The World Unified School District vs. California
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual white student percentage from 2022 to 2023 for Citizens Of The World Charter School East Valley School District vs. California
Map of the Vegetation of Africa by White.
ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
License information was derived automatically
Datasets Description:
The datasets under discussion pertain to the red and white variants of Portuguese "Vinho Verde" wine. Detailed information is available in the reference by Cortez et al. (2009). These datasets encompass physicochemical variables as inputs and sensory variables as outputs. Notably, specifics regarding grape types, wine brand, and selling prices are absent due to privacy and logistical concerns.
Classification and Regression Tasks: One can interpret these datasets as being suitable for both classification and regression analyses. The classes are ordered, albeit imbalanced. For instance, the dataset contains a more significant number of normal wines compared to excellent or poor ones.
Dataset Contents: For a comprehensive understanding, readers are encouraged to review the work by Cortez et al. (2009). The input variables, derived from physicochemical tests, include: 1. Fixed acidity 2. Volatile acidity 3. Citric acid 4. Residual sugar 5. Chlorides 6. Free sulfur dioxide 7. Total sulfur dioxide 8. Density 9. pH 10. Sulphates 11. Alcohol
The output variable, based on sensory data, is denoted by: 12. Quality (score ranging from 0 to 10)
Usage Tips: A practical suggestion involves setting a threshold for the dependent variable, defining wines with a quality score of 7 or higher as 'good/1' and the rest as 'not good/0.' This facilitates meaningful experimentation with hyperparameter tuning using decision tree algorithms and analyzing ROC curves and AUC values.
Operational Workflow: To efficiently utilize the dataset, the following steps are recommended: 1. Utilize a File Reader (for csv) to a linear correlation node and an interactive histogram for basic Exploratory Data Analysis (EDA). 2. Employ a File Reader to a Rule Engine Node for transforming the 10-point scale to a dichotomous variable indicating 'good wine' and 'rest.' 3. Implement a Rule Engine Node output to an input of Column Filter node to filter out the original 10-point feature, thus preventing data leakage. 4. Apply a Column Filter Node output to the input of Partitioning Node to execute a standard train/test split (e.g., 75%/25%, choosing 'random' or 'stratified'). 5. Feed the Partitioning Node train data split output into the input of Decision Tree Learner node. 6. Connect the Partitioning Node test data split output to the input of Decision Tree predictor Node. 7. Link the Decision Tree Learner Node output to the input of Decision Tree Node. 8. Finally, connect the Decision Tree output to the input of ROC Node for model evaluation based on the AUC value.
Tools and Acknowledgments: For an efficient analysis, consider using KNIME, a valuable graphical user interface (GUI) tool. Additionally, the dataset is available on the UCI machine learning repository, and proper acknowledgment and citation of the dataset source by Cortez et al. (2009) are essential for use.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual white student percentage from 2007 to 2023 for New World High School vs. New York and New York City Geographic District #11 School District
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual white student percentage from 2013 to 2023 for Meridian World School Llc vs. Texas and Meridian World School LLC School District
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Abstract: A multispectral light field dataset of three real-world highly textured scenes. TechnicalInfo: The dataset "DATA.zip" contains the decoded, white-balanced, and de-vignetted multispectral light fields. You can directly use these calibrated light fields in your research. If you do so, please cite our corresponding paper [1]. For further details, please see the provided README.txt. Other: [1] Maximilian Schambach, Jiayang Shi, and Michael Heizmann: "Spectral Reconstruction and Disparity from Spatio-Spectrally Coded Light Fields via Multi-Task Deep Learning" International Conference on 3D vision (3DV), 2021
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual white student percentage from 2015 to 2023 for Citizens Of The World Charter School 2 vs. New York and Citizens Of The World Charter School 2 School District
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual white student percentage from 2007 to 2023 for High School Of World Cultures vs. New York and New York City Geographic District #12 School District
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Non-Hispanic population of White Earth township by race. It includes the distribution of the Non-Hispanic population of White Earth township across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of White Earth township across relevant racial categories.
Key observations
Of the Non-Hispanic population in White Earth township, the largest racial group is American Indian and Alaska Native alone with a population of 437 (50.11% of the total Non-Hispanic population).
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for White Earth township Population by Race & Ethnicity. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual white student percentage from 2003 to 2023 for New World Educational Center vs. Arizona and New World Educational Center (78882) School District
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of White Earth township by race. It includes the population of White Earth township across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of White Earth township across relevant racial categories.
Key observations
The percent distribution of White Earth township population by race (across all racial categories recognized by the U.S. Census Bureau): 33.37% are white, 46% are American Indian and Alaska Native, 0.95% are Asian and 19.68% are multiracial.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for White Earth township Population by Race & Ethnicity. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Non-Hispanic population of White Earth by race. It includes the distribution of the Non-Hispanic population of White Earth across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of White Earth across relevant racial categories.
Key observations
With a zero Hispanic population, White Earth is 100% Non-Hispanic. Among the Non-Hispanic population, the largest racial group is White alone with a population of 76 (100% of the total Non-Hispanic population).
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for White Earth Population by Race & Ethnicity. You can refer the same here