Context

This dataset contains daily stock data for Meta Platforms, Inc. (META), formerly Facebook Inc., from May 19, 2012, to January 20, 2025. It offers a comprehensive view of Meta’s stock performance and market fluctuations during a period of significant growth, acquisitions, and technological advancements. This dataset is valuable for financial analysis, market prediction, machine learning projects, and evaluating the impact of Meta’s business decisions on its stock price.

Content

The dataset includes the following key features:

Open: Stock price at the start of the trading day. High: Highest stock price during the trading day. Low: Lowest stock price during the trading day. Close: Stock price at the end of the trading day. Adj Close: Adjusted closing price, accounting for corporate actions like stock splits, dividends, and other financial adjustments. Volume: Total number of shares traded during the trading day.

Variables

Date: The date of the trading day, formatted as YYYY-MM-DD. Open: The stock price at the start of the trading day. High: The highest price reached by the stock during the trading day. Low: The lowest price reached by the stock during the trading day. Close: The stock price at the end of the trading day. Adj Close: The adjusted closing price, which reflects corporate actions like stock splits and dividend payouts. Volume: The total number of shares traded on that specific day.

Acknowledgements

This dataset was sourced from reliable public APIs such as Yahoo Finance or Alpha Vantage. It is provided for educational and research purposes and is not affiliated with Meta Platforms, Inc. Users are encouraged to adhere to the terms of use of the original data provider.

We conduct a comprehensive literature review and meta-analysis of studies that examine the effects of water quality on waterfront and non-waterfront housing values. We identify 36 studies that yield 665 observations. The rows of the dataset include each observation from the hedonic studies and the columns include the variables we created from each study (e.g., year of publication, type of publication, water quality measure, _location, waterbody type, elasticities).

A dataset of datasets for learning to learn from few examples.

Describe your research hypothesis, what your data shows, any notable findings and how the data can be interpreted. Please add sufficient description to enable others to understand what the data is, how it was gathered and how to interpret and use it.

Meta learning with LLM: supplemental code for reproducibility of computational results for MLT and MLT-plus-TM. Related research paper: "META LEARNING WITH LANGUAGE MODELS: CHALLENGES AND OPPORTUNITIES IN THE CLASSIFICATION OF IMBALANCED TEXT", A. Vassilev, H. Jin, M. Hasan, 2023 (to appear on arXiv).All code and data is contained in the zip archive arxiv2023.zip, subject to the licensing terms shown below. See the Readme.txt contained there for detailed explanation how to unpack and run the code. See also requirements.txt for the necessary depedencies (libraries needed). This is not a dataset, but only python source code.

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This dataset is about companies. It has 17 rows and is filtered where the company is Meta. It features 5 columns: employees, CEO, CEO gender, and CEO approval.

Meta

## Overview

Meta is a dataset for object detection tasks - it contains YOLO annotations for 3,000 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).

Cross-platform Election Advertising Transparency Initiative (CREATIVE): dataset of fields pulled from Meta through keyword-based identification of all pages whose advertising possibly mentions 2022 federal candidates for office. It also includes creative elements extracted from audiovisual ads, including video transcriptions and overlaid text to images and videos.For more information, please visit our website: https://www.creativewmp.com/.The Variable Description Table file contains brief descriptions for each variable in the dataset. The Variable Description Table is identical across all four repositories, so it only needs to be downloaded once.

From OpenML we retrieved data from an earlier meta-learning study (Details can be found on https://www.openml.org/s/7). Although we had to exclude a few tasks and algorithms because they lacked sufficient evaluations in OpenML, this yielded a set of 10840 evaluations on 351 tasks (datasets) and 53 machine learning methods (called flows on OpenML) from mlr (Bischl et al., 2016). From each task, 21 dataset descriptors were extracted, such as the number of examples, number of missing values, and percentage of numeric features. We formed meta-datasets, one for each machine learning method. An observation within a meta-dataset represents an original OpenML task, and each feature, a dataset descriptor. The original aim of the study was to predict the area under the ROC (AUC). Therefore, in total, we produced 53 meta-datasets with a diverse number of OpenML tasks, ranging from above 100 to about 250.

About this dataset

Context

The dataset tabulates the Meta population by age. The dataset can be utilized to understand the age distribution and demographics of Meta.

Content

The dataset constitues the following three datasets

• Meta, MO Age Group Population Dataset: A complete breakdown of Meta age demographics from 0 to 85 years, distributed across 18 age groups
• Meta, MO Age Cohorts Dataset: Children, Working Adults, and Seniors in Meta - Population and Percentage Analysis
• Meta, MO Population Pyramid Dataset: Age Groups, Male and Female Population, and Total Population for Demographics Analysis

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/.

Meta Open Materials 2024 (OMat24) Dataset

  Overview

Several datasets were utilized in this work. We provide open access to all datasets used to help accelerate research in the community. This includes the OMat24 dataset as well as our modified sAlex dataset. Details on the different datasets are provided below. The OMat24 datasets can be used with the FAIRChem package. See section on "How to read the data" below for a minimal example.

  Datasets







  OMat24… See the full description on the dataset page: https://huggingface.co/datasets/facebook/OMAT24.

Dataset Card for Meta Evaluation Result Details for Llama-3.2-1B

This dataset contains the results of the Meta evaluation result details for Llama-3.2-1B. The dataset has been created from 8 evaluation tasks. The tasks are: needle_in_haystack, mmlu, squad, quac, drop, arc_challenge, multi_needle, agieval_english. Each task detail can be found as a specific subset in each configuration nd each subset is named using the task name plus the timestamp of the upload time and ends with… See the full description on the dataset page: https://huggingface.co/datasets/meta-llama/Llama-3.2-1B-evals.

Descriptions of data derived from previously published studies and used in a meta-analysis as desribed in "Prey responses to direct and indirect predation risk cues reveal the importance of multiple information sources."

Research Data

About this dataset

Context

The dataset tabulates the Meta population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Meta. The dataset can be utilized to understand the population distribution of Meta by age. For example, using this dataset, we can identify the largest age group in Meta.

Key observations

The largest age group in Meta, MO was for the group of age 65 to 69 years years with a population of 18 (14.06%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Meta, MO was the 20 to 24 years years with a population of 0 (0%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Meta is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Meta total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Meta Population by Age. You can refer the same here

patricknasr/addresso-dataset-meta dataset hosted on Hugging Face and contributed by the HF Datasets community

Background Meta-analysis is often considered to be a simple way to summarize the existing literature. In this paper we describe how a meta-analysis resembles a conventional study, requiring a written protocol with design elements that parallel those of a record review. Methods The paper provides a structure for creating a meta-analysis protocol. Some guidelines for measurement of the quality of papers are given. A brief overview of statistical considerations is included. Four papers are reviewed as examples. The examples generally followed the guidelines we specify in reporting the studies and results, but in some of the papers there was insufficient information on the meta-analysis process. Conclusions Meta-analysis can be a very useful method to summarize data across many studies, but it requires careful thought, planning and implementation.

This dataset is about stocks. It has 1 row and is filtered where the company is Meta Health. It features 8 columns including stock name, company, exchange, and exchange symbol.

Ebitda Time Series for Meta Platforms Inc.. Meta Platforms, Inc. engages in the development of products that enable people to connect and share with friends and family through mobile devices, personal computers, virtual reality and mixed reality headsets, augmented reality, and wearables worldwide. It operates through two segments, Family of Apps (FoA) and Reality Labs (RL). The FoA segment offers Facebook, which enables people to build community through feed, reels, stories, groups, marketplace, and other; Instagram that brings people closer through instagram feed, stories, reels, live, and messaging; Messenger, a messaging application for people to connect with friends, family, communities, and businesses across platforms and devices through text, audio, and video calls; Threads, an application for text-based updates and public conversations; and WhatsApp, a messaging application that is used by people and businesses to communicate and transact in a private way. The RL segment provides virtual, augmented, and mixed reality related products comprising consumer hardware, software, and content that help people feel connected, anytime, and anywhere. The company was formerly known as Facebook, Inc. and changed its name to Meta Platforms, Inc. in October 2021. The company was incorporated in 2004 and is headquartered in Menlo Park, California.