Image Classification Age Range Labels

This repository uses the following labels to categorize age ranges in image classification tasks:

[!Warning] labels_list = ['0-12', '13-20', '21-44', '45-64', '65+']

the values are age range in iamge classification give the README.MD for Repository

0-12: Images depicting individuals aged 0 to 12 years old. 13-20: Images depicting individuals aged 13 to 20 years old. 21-44: Images depicting individuals aged 21 to 44 years old. 45-64: Images… See the full description on the dataset page: https://huggingface.co/datasets/prithivMLmods/Age-Classification-Set.

Provides information highlights by topic via key indicators for various levels of geography.

Feature set developed to support "Predicting Age Groups of Twitter Users Based on Language and Metadata Features" by Morgan-Lopez et al. (2017). The feature set encompasses candidate variables for each of the four models referenced in the paper ("Tweet Language Only","Twitter Handle Metadata Only","Tweet Language Use and Handle Metadata", and "WWBP Words"). Description of target variables listed below -- for further description of features and methodology please reference manuscript.Target Variablesage_cat: User age category {"1" : 13-17, "2" : 18-24, "3" : 25-50} age_cat_sen: User age category used for sensitivity analysis {"1" : 13-17, "2" : 18-29, "3" : 30-50}user_age: User ageOtherrand_id: Random ID assigned to Twitter user

Age Range Classification

## Overview

Age Range Classification is a dataset for classification tasks - it contains 1 2 3 4 5 annotations for 9,794 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Estimate Population By Category Of Patients & Age Groups By State 2018-2020 Notes: 1. Data for live birth CURRENT year is not yet available from Department of Statistics, Malaysia (DOSM). Therefore, data for PREVIOUS year is provided for reference. 2. P - Preliminary figure 3. The added total differ due to rounding. (1) Current Population Estimates (related year) (2) Primary & Secondary School enrolment (PG 203 & PG204) (3) Data calculated by HIC (3)(b) Input for calculating Estimated number of antenatal mothers is number of live births. Therefore, the estimated number of antenatal mothers is based on previous year live births. (4)(b) Estimated number of antenatal mothers based on new attendances to MCHC. Sources: (a) Department of Statistics, Malaysia (b) Health Informatics Centre, Planning Division, MOH No. of Views : 217

When comparing by age the products which will be purchased on Amazon Prime Day in 2022, one can see that the share of 18 to 34 year olds planning to make purchases is greater than the other two age groups listed for nearly every product category. For the older age groups, products for the home and other items not listed are the two product categories most likely to be purchased on Amazon Prime Day, while the youngest age group is more likely to buy makeup and skincare products.

Curious about age demographics of your clientele in United Kingdom? Wondering about which generation can be most often seen flocking to your store? Dive deep into customer insights using our population by age group data of United Kingdom. Whether your customers are down your street or across the globe, we empower you to pinpoint the ideal demographic for your marketing campaigns or projects. Our dataset offers intricate details on this country's age distribution.

Age Classification

## Overview

Age Classification is a dataset for classification tasks - it contains Age Groups annotations for 2,772 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

age grouping categories - ARCHIVED For the new LA City Events dataset (refreshed daily), see https://data.lacity.org/A-Prosperous-City/LA-City-Events/rx9t-fp7k

Per a 2023 survey by Rakuten Insight on user-generated content (UGC), Indian consumers between the ages of ** and ** primarily consumed UGC related to the beauty, health, and wellness category, reflected in more than ** percent of the responses. It was also noteworthy that ** percent of consumers aged over 55 years were interested in electronics and home goods-related UGC.

Table from the American Community Survey (ACS) B01001A-I sex by age by race - data is grouped into three age group categories for each race, under 18, 18-64 and 65 and older. These are multiple, nonoverlapping vintages of the 5-year ACS estimates of population and housing attributes starting in 2010 shown by the corresponding census tract vintage. Also includes the most recent release annually.Data on total number of people by each race alone and in combination by each census tract has been transposed to support dashboard visualizations.King County, Washington census tracts with nonoverlapping vintages of the 5-year American Community Survey (ACS) estimates starting in 2010. Vintage identified in the "ACS Vintage" field.The census tract boundaries match the vintage of the ACS data (currently 2010 and 2020) so please note the geographic changes between the decades. Tracts have been coded as being within the City of Seattle as well as assigned to neighborhood groups called "Community Reporting Areas". These areas were created after the 2000 census to provide geographically consistent neighborhoods through time for reporting U.S. Census Bureau data. This is not an attempt to identify neighborhood boundaries as defined by neighborhoods themselves.Vintages: 2010, 2015, 2020, 2021, <a href='https://www.census.gov/programs-surveys/acs/news/data-releases/2022/release.html#5yr' style='font-famil

Estimate Population By Category Of Patients & Age Groups By State Malaysia, 2016

Classification by causes, age groups and sex. National. Classification by causes in combination with age groups and sex.

An Open Context "predicates" dataset item. Open Context publishes structured data as granular, URL identified Web resources. This "Variables" record is part of the "Domuztepe Excavations" data publication.

This layer shows age and sex demographics. Data is from US Census American Community Survey (ACS) 5-year estimates.This layer is symbolized to the percent of the population ages 18 to 24 years old. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right (in ArcGIS Online). To view only the census tracts that are predominantly in Tempe, add the expression City is Tempe in the filter settings. Layer includes:Key demographicsTotal populationMale total populationFemale total populationPercent male total population (calculated)Percent female total population (calculated)Age and other indicatorsTotal population by AGE (various ranges)Total population by SELECTED AGE CATEGORIES (various ranges)Total population by SUMMARY INDICATORS (including median age, sex ratio, age dependency ratio, old age dependency ratio, child dependency ratio)Percent total population by AGE (various ranges)Percent total population by SELECTED AGE CATEGORIES (various ranges)Male by ageMale total population by AGE (various ranges)Male total population by SELECTED AGE CATEGORIES (various ranges)Male total population Median age (years)Percent male total population by AGE (various ranges)Percent male total population by SELECTED AGE CATEGORIES (various ranges)Female by ageFemale total population by AGE (various ranges)Female total population by SELECTED AGE CATEGORIES (various ranges)Female total population Median age (years)Percent female total population by AGE (various ranges)Percent female total population by SELECTED AGE CATEGORIES (various ranges)A ‘Null’ entry in the estimate indicates that data for this geographic area cannot be displayed because the number of sample cases is too small (per the U.S. Census).Current Vintage: 2018-2022ACS Table(s): S0101 (Not all lines of this ACS table are available in this feature layer.)Data downloaded from: Census Bureau's API for American Community SurveyDate of Census update: Dec 15, 2023Data Preparation: Data table downloaded and joined with Census Tract boundaries that are within or adjacent to the City of Tempe boundaryNational Figures: data.census.gov

Classification by methods used, age groups and sex. National. Classification by methods used in combination with age groups and sex.

The dataset shows, for the year 2014, the subdivision of the Municipality's permanent staff by category (A, B1, B3, C, D1, D3) and by age group. The following age groups are proposed: * 20-24 years * 25-29 years * 30-34 years * 35-39 years * 40-44 years * 45-49 years * 50-54 years * 55-59 years * 60-64 years old * 65 and over This dataset was released by the municipality of Milan through two different csv files, one in tabular format and one in pivot format.

During the second quarter of 2022, ****** apps hosted and distributed in the Google Play Store registered higher engagement among global users aged between 18 and 24 years. ******* users were the most active demographic across all examined app categories, with approximately **** of all downloads in the music and audio category generated in the Google Play Store coming from users in the 18 to 24 demographic group. Approximately ***** in ** users downloading news and magazines apps were aged between 50 and 64 years, while ***percent of parenting apps were downloaded by users aged 25 and 34 years.

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Viola: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..

Key observations

• Upon closer examination of the distribution of households among age brackets, it reveals that there are 1(0.98%) households where the householder is under 25 years old, 71(69.61%) households with a householder aged between 25 and 44 years, 11(10.78%) households with a householder aged between 45 and 64 years, and 19(18.63%) households where the householder is over 65 years old.
• In Viola, the age group of 25 to 44 years stands out with both the highest median income and the maximum share of households. This alignment suggests a financially stable demographic, indicating an established community with stable careers and higher incomes.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Income brackets:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $100,000 to $124,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Household Income: This column showcases 16 income brackets ranging from Under $10,000 to $200,000+ ( As mentioned above).
• Under 25 years: The count of households led by a head of household under 25 years old with income within a specified income bracket.
• 25 to 44 years: The count of households led by a head of household 25 to 44 years old with income within a specified income bracket.
• 45 to 64 years: The count of households led by a head of household 45 to 64 years old with income within a specified income bracket.
• 65 years and over: The count of households led by a head of household 65 years and over old with income within a specified income bracket.

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for Viola median household income by age. You can refer the same here

This table provides annual data on the estimated population aged 16 and over in the Canary Islands by activity and age groups.