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Your Benefits:
π Explore global resources!
π± Test app localization!
π Research your competitors!
π Enhance your privacy & security!
π§ Check network infrastructures!
π Bypass ISP restrictions!
π Access regional contents!
Save via this link ONLY! Hurry up !
*Best for developers. Do not forget to paste "Developers30" promo code.
π https://macpaw.audw.net/Developers30
π10
Mask dataset without filters.zip
191.1 MB
π¦ Datasets name: Mask dataset without filters
β Format: Images files
π From: Kaggle
π’ https://t.me/datasets1
β Format: Images files
π From: Kaggle
π’ https://t.me/datasets1
π14β€4
Job postings.zip
315.3 KB
π¦ Datasets name: Job postings
π¬ Categorized Roles with Detailed Descriptions, Benefits, and requirements
β Format: CSV files
π From: Kaggle
π’ https://t.me/datasets1
π¬ Categorized Roles with Detailed Descriptions, Benefits, and requirements
β Format: CSV files
π From: Kaggle
π’ https://t.me/datasets1
π14π1
pinterest_finalised.zip
205.4 KB
π¦ Datasets name: pinterest finalised
π¬ Top Pinterest Influencers - A Snapshot of Popularity and Engagement
β Format: CSV file
π From: Kaggle
π’ https://t.me/datasets1
π¬ Top Pinterest Influencers - A Snapshot of Popularity and Engagement
β Format: CSV file
π From: Kaggle
π’ https://t.me/datasets1
π7β€1π1
Which website do you prefer the datasets to be from?
Anonymous Poll
23%
UCI Machine Learning repository
13%
Microsoftβs datasets
12%
Amazon datasets
53%
Kaggle
π9π₯4π2π1
Emotions .csv
42.8 MB
π¦ Datasets name: Emotions
π¬ a collection of English Twitter messages meticulously annotated with six fundamental emotions: anger, fear, joy, love, sadness, and surprise. This dataset serves as a valuable resource for understanding and analyzing the diverse spectrum of emotions expressed in short-form text on social media.
β Format: CSV file
π From: Kaggle
π’ https://t.me/datasets1
π¬ a collection of English Twitter messages meticulously annotated with six fundamental emotions: anger, fear, joy, love, sadness, and surprise. This dataset serves as a valuable resource for understanding and analyzing the diverse spectrum of emotions expressed in short-form text on social media.
β Format: CSV file
π From: Kaggle
π’ https://t.me/datasets1
PC Parts Images Dataset.zip
34.1 MB
π¦ Datasets name: PC Parts Images Dataset
β Format: Images files
π From: Kaggle
π’ https://t.me/datasets1
β Format: Images files
π From: Kaggle
π’ https://t.me/datasets1
π13π₯2π³2π€1
Top YouTubers Worldwide.zip
83.4 KB
π¦ Datasets name: Top YouTubers Worldwide
π¬ This dataset provides detailed metrics and categories for a diverse range of popular YouTube channels. Explore key statistics such as subscriber count, video views, category, and geographical information for each channel. Ideal for analysis and insights into trends within the dynamic landscape of online content creation.
β Format: CSV file
π From: Kaggle
π’ https://t.me/datasets1
π¬ This dataset provides detailed metrics and categories for a diverse range of popular YouTube channels. Explore key statistics such as subscriber count, video views, category, and geographical information for each channel. Ideal for analysis and insights into trends within the dynamic landscape of online content creation.
β Format: CSV file
π From: Kaggle
π’ https://t.me/datasets1
π12β€1π1
NHANES_2017-2018.zip
11.7 MB
π¦ Datasets name: National Health & Nutrition Exam Survey 2017-2018
π¬ this is the most recent NHANES dataset whose data collection was not affected by COVID-19.
β Format: CSV file
π From: Kaggle
π’ https://t.me/datasets1
π¬ this is the most recent NHANES dataset whose data collection was not affected by COVID-19.
β Format: CSV file
π From: Kaggle
π’ https://t.me/datasets1
π8
In which area do you prefer datasets to be placed in the channel?
Anonymous Poll
8%
Sound processing
12%
Video processing
51%
Natural Language Processing
29%
Image Processing
π€8π₯3π€©2
Car F and P.csv
1.4 MB
π¦ Datasets name: Car Features and Prices Dataset
π¬ This dataset which has different features of cars like model, year, engine and other properties along with its price. It has 28 years of data from 1990 to 2017.
β Format: CSV file
π From: Kaggle
π’ https://t.me/datasets1
π¬ This dataset which has different features of cars like model, year, engine and other properties along with its price. It has 28 years of data from 1990 to 2017.
β Format: CSV file
π From: Kaggle
π’ https://t.me/datasets1
π15π€©3
NFLX.csv
18.2 KB
π¦ Datasets name: Netflix stock price data for 2023-24.
π¬Netflix's stock prices, spanning from 2023 to 2024. It is an invaluable resource for data analysts and financial experts, enabling them to perform regression analysis, predict future trends, and create insightful data visualizations. With this dataset, users can gain a deeper understanding of how Netflix's stock prices over time, and use this knowledge to make informed decisions about investments and financial strategies.
β Format: CSV file
π From: Kaggle
π’ https://t.me/datasets1
π¬Netflix's stock prices, spanning from 2023 to 2024. It is an invaluable resource for data analysts and financial experts, enabling them to perform regression analysis, predict future trends, and create insightful data visualizations. With this dataset, users can gain a deeper understanding of how Netflix's stock prices over time, and use this knowledge to make informed decisions about investments and financial strategies.
β Format: CSV file
π From: Kaggle
π’ https://t.me/datasets1
π16
preprocessed_airline_dataset.csv
1.4 MB
π¦ Datasets name: British Airways Review Dataset(2012-2023)
π¬Skytrax dataset for British airways
β Format: CSV file
π From: Kaggle
π’ https://t.me/datasets1
π¬Skytrax dataset for British airways
β Format: CSV file
π From: Kaggle
π’ https://t.me/datasets1
π12π€©2
breast-cancer-wisconsin-data.csv
122.2 KB
π¦ Datasets name: Breast Cancer Dataset [Wisconsin Diagnostic UCI]
π¬Predict Breast Cancer with ML: A guide to the Wisconsin Diagnostic Dataset - Breast cancer is when breast cells mutate and become cancerous cells that multiply and form tumors. It accounts for 25% of all cancer cases and affected over 2.1 Million people in 2015 alone. Breast cancer typically affects women and people assigned female at birth (AFAB) age 50 and older, but it can also affect men and people assigned male at birth (AMAB), as well as younger women. Healthcare providers may treat breast cancer with surgery to remove tumors or treatment to kill cancerous cells.
Features are computed from a digitized image of a fine needle aspirate (FNA) of a breast mass. They describe characteristics of the cell nuclei present in the image.
β Format: CSV file
π From: Kaggle
π’ https://t.me/datasets1
π¬Predict Breast Cancer with ML: A guide to the Wisconsin Diagnostic Dataset - Breast cancer is when breast cells mutate and become cancerous cells that multiply and form tumors. It accounts for 25% of all cancer cases and affected over 2.1 Million people in 2015 alone. Breast cancer typically affects women and people assigned female at birth (AFAB) age 50 and older, but it can also affect men and people assigned male at birth (AMAB), as well as younger women. Healthcare providers may treat breast cancer with surgery to remove tumors or treatment to kill cancerous cells.
Features are computed from a digitized image of a fine needle aspirate (FNA) of a breast mass. They describe characteristics of the cell nuclei present in the image.
β Format: CSV file
π From: Kaggle
π’ https://t.me/datasets1
π23β€4
Tumor.zip
83.7 MB
π¦ Datasets name: Brain Tumor Image DataSet : Semantic Segmentation
π¬The Tumor Segmentation Dataset is designed specifically for the TumorSeg Computer Vision Project, which focuses on Semantic Segmentation. The project aims to identify tumor regions accurately within Medical Images using advanced techniques.
β Format: Images files
π From: Kaggle
π’ https://t.me/datasets1
π¬The Tumor Segmentation Dataset is designed specifically for the TumorSeg Computer Vision Project, which focuses on Semantic Segmentation. The project aims to identify tumor regions accurately within Medical Images using advanced techniques.
β Format: Images files
π From: Kaggle
π’ https://t.me/datasets1
π13β€4π1
heart+disease.zip
125.9 KB
π¦ Datasets name: Heart Disease
π¬ This database contains 76 attributes, but all published experiments refer to using a subset of 14 of them. In particular, the Cleveland database is the only one that has been used by ML researchers to date. The "goal" field refers to the presence of heart disease in the patient. It is integer valued from 0 (no presence) to 4. Experiments with the Cleveland database have concentrated on simply attempting to distinguish presence (values 1,2,3,4) from absence (value 0). The names and social security numbers of the patients were recently removed from the database, replaced with dummy values. One file has been "processed", that one containing the Cleveland database. All four unprocessed files also exist in this directory. To see Test Costs (donated by Peter Turney), please see the folder "Costs"
π From: UCI Machine Learning repository
π’ https://t.me/datasets1
π¬ This database contains 76 attributes, but all published experiments refer to using a subset of 14 of them. In particular, the Cleveland database is the only one that has been used by ML researchers to date. The "goal" field refers to the presence of heart disease in the patient. It is integer valued from 0 (no presence) to 4. Experiments with the Cleveland database have concentrated on simply attempting to distinguish presence (values 1,2,3,4) from absence (value 0). The names and social security numbers of the patients were recently removed from the database, replaced with dummy values. One file has been "processed", that one containing the Cleveland database. All four unprocessed files also exist in this directory. To see Test Costs (donated by Peter Turney), please see the folder "Costs"
π From: UCI Machine Learning repository
π’ https://t.me/datasets1
π18π₯3β€1
dry+bean+dataset.zip
4.5 MB
π¦ Datasets name: Dry Bean Dataset
π¬ Seven different types of dry beans were used in this research, taking into account the features such as form, shape, type, and ...
π From: UCI Machine Learning repository
#Biology #Classification
π’ https://t.me/datasets1
π¬ Seven different types of dry beans were used in this research, taking into account the features such as form, shape, type, and ...
π From: UCI Machine Learning repository
#Biology #Classification
π’ https://t.me/datasets1
π11π2β€1π₯1
adult.zip
605.7 KB
π¦ Datasets name: Adult
π¬ Extraction was done by Barry Becker from the 1994 Census database. A set of reasonably clean records was extracted using the following conditions: ((AAGE>16) && (AGI>100) && (AFNLWGT>1)&& (HRSWK>0))
Prediction task is to determine whether a person makes over 50K a year.
π From: UCI Machine Learning repository
#Social_Science #Classification
π’ https://t.me/datasets1
π¬ Extraction was done by Barry Becker from the 1994 Census database. A set of reasonably clean records was extracted using the following conditions: ((AAGE>16) && (AGI>100) && (AFNLWGT>1)&& (HRSWK>0))
Prediction task is to determine whether a person makes over 50K a year.
π From: UCI Machine Learning repository
#Social_Science #Classification
π’ https://t.me/datasets1
π33β€5β€βπ₯1π₯1π€1
TopSongs.zip
436.2 KB
π¦ Datasets name: Top Songs of the World
π¬ "Top Songs of the World" is a collection of information about popular songs spanning various decades and genres. The dataset includes details such as the ranking of songs, the respective artists, titles, release years, sales figures, streaming statistics, download counts, radio play metrics, and a numerical rating. This dataset provides insights into the commercial success, digital presence, and overall popularity of each song, offering a comprehensive overview of the music industry's landscape over time. Researchers, analysts, and music enthusiasts can utilize this dataset to explore trends, patterns, and correlations within the context of the featured songs and artists.
β Format: CSV file
π From: Kaggle
π’ https://t.me/datasets1
π¬ "Top Songs of the World" is a collection of information about popular songs spanning various decades and genres. The dataset includes details such as the ranking of songs, the respective artists, titles, release years, sales figures, streaming statistics, download counts, radio play metrics, and a numerical rating. This dataset provides insights into the commercial success, digital presence, and overall popularity of each song, offering a comprehensive overview of the music industry's landscape over time. Researchers, analysts, and music enthusiasts can utilize this dataset to explore trends, patterns, and correlations within the context of the featured songs and artists.
β Format: CSV file
π From: Kaggle
π’ https://t.me/datasets1
π20
Spotify's Greatest.zip
345.4 KB
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