International football results from 1872 to 2024
An up-to-date dataset of over 47,000 international football results
Context
Well, what happened was that I was looking for a semi-definite easy-to-read list of international football matches and couldn't find anything decent. So I took it upon myself to collect it for my own use. I might as well share it.
Content
This dataset includes 47,917 results of international football matches starting from the very first official match in 1872 up to 2024. The matches range from FIFA World Cup to FIFI Wild Cup to regular friendly matches. The matches are strictly men's full internationals and the data does not include Olympic Games or matches where at least one of the teams was the nation's B-team, U-23 or a league select team.
results.csv includes the following columns:
date - date of the match
home_team - the name of the home team
away_team - the name of the away team
home_score - full-time home team score including extra time, not including penalty-shootouts
away_score - full-time away team score including extra time, not including penalty-shootouts
tournament - the name of the tournament
city - the name of the city/town/administrative unit where the match was played
country - the name of the country where the match was played
neutral - TRUE/FALSE column indicating whether the match was played at a neutral venue
shootouts.csv includes the following columns:
date - date of the match
home_team - the name of the home team
away_team - the name of the away team
winner - winner of the penalty-shootout
first_shooter - the team that went first in the shootout
goalscorers.csv includes the following columns:
date - date of the match
home_team - the name of the home team
away_team - the name of the away team
team - name of the team scoring the goal
scorer - name of the player scoring the goal
own_goal - whether the goal was an own-goal
penalty - whether the goal was a penalty
https://news.1rj.ru/str/datasets1🖕
An up-to-date dataset of over 47,000 international football results
Context
Well, what happened was that I was looking for a semi-definite easy-to-read list of international football matches and couldn't find anything decent. So I took it upon myself to collect it for my own use. I might as well share it.
Content
This dataset includes 47,917 results of international football matches starting from the very first official match in 1872 up to 2024. The matches range from FIFA World Cup to FIFI Wild Cup to regular friendly matches. The matches are strictly men's full internationals and the data does not include Olympic Games or matches where at least one of the teams was the nation's B-team, U-23 or a league select team.
results.csv includes the following columns:
date - date of the match
home_team - the name of the home team
away_team - the name of the away team
home_score - full-time home team score including extra time, not including penalty-shootouts
away_score - full-time away team score including extra time, not including penalty-shootouts
tournament - the name of the tournament
city - the name of the city/town/administrative unit where the match was played
country - the name of the country where the match was played
neutral - TRUE/FALSE column indicating whether the match was played at a neutral venue
shootouts.csv includes the following columns:
date - date of the match
home_team - the name of the home team
away_team - the name of the away team
winner - winner of the penalty-shootout
first_shooter - the team that went first in the shootout
goalscorers.csv includes the following columns:
date - date of the match
home_team - the name of the home team
away_team - the name of the away team
team - name of the team scoring the goal
scorer - name of the player scoring the goal
own_goal - whether the goal was an own-goal
penalty - whether the goal was a penalty
https://news.1rj.ru/str/datasets1
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archive.zip
1.1 MB
International football results from 1872 to 2024
#Datasets #Kaggle #MachineLearning #Python #ML #LLM #NLP #ComputerVision #GPT4
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#Datasets #Kaggle #MachineLearning #Python #ML #LLM #NLP #ComputerVision #GPT4
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WLU Rehabilitation Posture
Exercises: Arm Raise, Knee Extension and Sit To Stand
The dataset includes videos recorded from multiple angles and devices, covering exercises such as arm raise, knee extension, and sit-to-stand. While testing our models, we used the original unblurred version of the dataset to ensure accuracy and performance.
#KaggleDatasets #DataScience #MachineLearning #DataAnalysis #DataVisualization #OpenData #DataCleaning #TextClassification #NLP #SentimentAnalysis #BigData #APIAutomation #DataLicensing #SocialMediaData #PythonIntegration #DataModeling #kaggle
https://news.1rj.ru/str/datasets1❤️
Exercises: Arm Raise, Knee Extension and Sit To Stand
The dataset includes videos recorded from multiple angles and devices, covering exercises such as arm raise, knee extension, and sit-to-stand. While testing our models, we used the original unblurred version of the dataset to ensure accuracy and performance.
#KaggleDatasets #DataScience #MachineLearning #DataAnalysis #DataVisualization #OpenData #DataCleaning #TextClassification #NLP #SentimentAnalysis #BigData #APIAutomation #DataLicensing #SocialMediaData #PythonIntegration #DataModeling #kaggle
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archive.zip
830.8 MB
WLU Rehabilitation Posture
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https://news.1rj.ru/str/datasets1✅
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Tappy Keystroke Data with Parkinson's Patients
Raw data used to predict the onset of Parkinson from typing tendencies
The dataset contains keystroke logs collected from over 200 subjects, with and without Parkinson's Disease (PD), as they typed normally on their own computer (without any supervision) over a period of weeks or months (having initially installed a custom keystroke recording app, Tappy). This dataset has been collected and analyzed in order to indicate that the routine interaction with computer keyboards can be used to detect changes in the characteristics of finger movement in the early stages of PD.
#KaggleDatasets #DataScience #MachineLearning #DataAnalysis #DataVisualization #OpenData #DataCleaning #TextClassification #NLP #SentimentAnalysis #BigData #APIAutomation #DataLicensing #SocialMediaData #PythonIntegration #DataModeling #kaggle #ComputerVision #python #LLM #DeepLearning #Pytorch
https://news.1rj.ru/str/datasets1✅
Raw data used to predict the onset of Parkinson from typing tendencies
The dataset contains keystroke logs collected from over 200 subjects, with and without Parkinson's Disease (PD), as they typed normally on their own computer (without any supervision) over a period of weeks or months (having initially installed a custom keystroke recording app, Tappy). This dataset has been collected and analyzed in order to indicate that the routine interaction with computer keyboards can be used to detect changes in the characteristics of finger movement in the early stages of PD.
#KaggleDatasets #DataScience #MachineLearning #DataAnalysis #DataVisualization #OpenData #DataCleaning #TextClassification #NLP #SentimentAnalysis #BigData #APIAutomation #DataLicensing #SocialMediaData #PythonIntegration #DataModeling #kaggle #ComputerVision #python #LLM #DeepLearning #Pytorch
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archive.zip
95.8 MB
Tappy Keystroke Data with Parkinson's Patients
#KaggleDatasets #DataScience #MachineLearning #DataAnalysis #DataVisualization #OpenData #DataCleaning #TextClassification #NLP #SentimentAnalysis #BigData #APIAutomation #DataLicensing #SocialMediaData #PythonIntegration #DataModeling #kaggle #ComputerVision #python #LLM #DeepLearning #Pytorch
https://news.1rj.ru/str/datasets1✅
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Alzheimer Parkinson Diseases 3 Class
Classify into 3 class - CONTROL, AD, PD
3_cls folder has 2 directories:
train
test
Each directory has 3 sub-directories:
CONTROL
AD
PD
#KaggleDatasets #DataScience #MachineLearning #DataAnalysis #DataVisualization #OpenData #DataCleaning #TextClassification #NLP #SentimentAnalysis #BigData #APIAutomation #DataLicensing #SocialMediaData #PythonIntegration #DataModeling #kaggle #ComputerVision #python #LLM #DeepLearning #Pytorch
https://news.1rj.ru/str/datasets1✅
Classify into 3 class - CONTROL, AD, PD
3_cls folder has 2 directories:
train
test
Each directory has 3 sub-directories:
CONTROL
AD
PD
#KaggleDatasets #DataScience #MachineLearning #DataAnalysis #DataVisualization #OpenData #DataCleaning #TextClassification #NLP #SentimentAnalysis #BigData #APIAutomation #DataLicensing #SocialMediaData #PythonIntegration #DataModeling #kaggle #ComputerVision #python #LLM #DeepLearning #Pytorch
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archive.zip
48.7 MB
Alzheimer Parkinson Diseases 3 Class
#KaggleDatasets #DataScience #MachineLearning #DataAnalysis #DataVisualization #OpenData #DataCleaning #TextClassification #NLP #SentimentAnalysis #BigData #APIAutomation #DataLicensing #SocialMediaData #PythonIntegration #DataModeling #kaggle #ComputerVision #python #LLM #DeepLearning #Pytorch
https://news.1rj.ru/str/datasets1✅
#KaggleDatasets #DataScience #MachineLearning #DataAnalysis #DataVisualization #OpenData #DataCleaning #TextClassification #NLP #SentimentAnalysis #BigData #APIAutomation #DataLicensing #SocialMediaData #PythonIntegration #DataModeling #kaggle #ComputerVision #python #LLM #DeepLearning #Pytorch
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Handwritten Mathematical Expression Convert LaTeX
The Azu/Handwritten-Mathematical-Expression-Convert-LaTeX dataset on Hugging Face is designed for converting handwritten mathematical expressions into LaTeX code. It includes image-text pairs, where each image contains a handwritten mathematical expression, and the corresponding text is its LaTeX representation. The dataset is suitable for training models in Handwritten Mathematical Expression Recognition (HMER) tasks, combining computer vision and natural language processing techniques.
With a size ranging between 10K to 100K samples, it supports tasks like image-to-sequence modeling and LaTeX code generation. The dataset is formatted as an imagefolder, making it easy to integrate into machine learning pipelines.
#KaggleDatasets #DataScience #MachineLearning #DataAnalysis #DataVisualization #OpenData #DataCleaning #TextClassification #NLP #SentimentAnalysis #BigData #APIAutomation #DataLicensing #SocialMediaData #PythonIntegration #DataModeling #kaggle #ComputerVision #python #LLM #DeepLearning #Pytorch #HuggingFace #Dataset
https://news.1rj.ru/str/datasets1🎁
The Azu/Handwritten-Mathematical-Expression-Convert-LaTeX dataset on Hugging Face is designed for converting handwritten mathematical expressions into LaTeX code. It includes image-text pairs, where each image contains a handwritten mathematical expression, and the corresponding text is its LaTeX representation. The dataset is suitable for training models in Handwritten Mathematical Expression Recognition (HMER) tasks, combining computer vision and natural language processing techniques.
With a size ranging between 10K to 100K samples, it supports tasks like image-to-sequence modeling and LaTeX code generation. The dataset is formatted as an imagefolder, making it easy to integrate into machine learning pipelines.
#KaggleDatasets #DataScience #MachineLearning #DataAnalysis #DataVisualization #OpenData #DataCleaning #TextClassification #NLP #SentimentAnalysis #BigData #APIAutomation #DataLicensing #SocialMediaData #PythonIntegration #DataModeling #kaggle #ComputerVision #python #LLM #DeepLearning #Pytorch #HuggingFace #Dataset
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Volleyball Ball Object Detection Dataset
Volleyball Court Images + Ball Object Detection Annotations
This dataset comprises volleyball court images and their ball object detection annotations.
The dataset has been annotated precisely to train a yolov8x model to detect the ball in volleyball matches.
This dataset is part of three datasets (the other two for volleyball players and referee object detection and volleyball court key points regression) used to train yolov8x models for my project.
#KaggleDatasets #DataScience #MachineLearning #DataAnalysis #DataVisualization #OpenData #DataCleaning #TextClassification #NLP #SentimentAnalysis #BigData #APIAutomation #DataLicensing #SocialMediaData #PythonIntegration #DataModeling #kaggle #ComputerVision #python #LLM #DeepLearning #Pytorch #HuggingFace #Dataset
https://news.1rj.ru/str/datasets1🎁
Volleyball Court Images + Ball Object Detection Annotations
This dataset comprises volleyball court images and their ball object detection annotations.
The dataset has been annotated precisely to train a yolov8x model to detect the ball in volleyball matches.
This dataset is part of three datasets (the other two for volleyball players and referee object detection and volleyball court key points regression) used to train yolov8x models for my project.
#KaggleDatasets #DataScience #MachineLearning #DataAnalysis #DataVisualization #OpenData #DataCleaning #TextClassification #NLP #SentimentAnalysis #BigData #APIAutomation #DataLicensing #SocialMediaData #PythonIntegration #DataModeling #kaggle #ComputerVision #python #LLM #DeepLearning #Pytorch #HuggingFace #Dataset
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Forwarded from Machine Learning with Python
LOOKING FOR A NEW SOURCE OF INCOME?
Average earnings from 100$ a day
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WHAT YOU NEED TO WORK:
1. phone or computer
2. Free 15-20 minutes a day
3. desire to earn
❗️ Requires 20 people ❗️
Access is available at the link below
👇
https://news.1rj.ru/str/+EWM2hR1d_As0ZDA5
Average earnings from 100$ a day
Lisa is looking for people who want to earn money. If you are responsible, motivated and want to change your life. Welcome to her channel.
WHAT YOU NEED TO WORK:
1. phone or computer
2. Free 15-20 minutes a day
3. desire to earn
❗️ Requires 20 people ❗️
Access is available at the link below
👇
https://news.1rj.ru/str/+EWM2hR1d_As0ZDA5
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Gender Recognition by Voice (processed)
help identifying male and female voice
Features:
The dataset includes the following extracted audio features:
mean_spectral_centroid: The average spectral centroid, representing the "center of mass" of the spectrum, indicating brightness.
std_spectral_centroid: The standard deviation of the spectral centroid, measuring variability in brightness.
mean_spectral_bandwidth: The average width of the spectrum, reflecting how spread out the frequencies are.
std_spectral_bandwidth: The standard deviation of spectral bandwidth, indicating variability in frequency spread.
mean_spectral_contrast: The average difference between peaks and valleys in the spectrum, indicating tonal contrast.
mean_spectral_flatness: The average flatness of the spectrum, measuring the noisiness of the signal.
mean_spectral_rolloff: The average frequency below which a specified percentage of the spectral energy resides, indicating sharpness.
zero_crossing_rate: The rate at which the signal crosses the zero amplitude axis, representing noisiness or percussiveness.
rms_energy: The root mean square energy of the signal, reflecting its loudness.
mean_pitch: The average pitch frequency of the audio.
min_pitch: The minimum pitch frequency.
max_pitch: The maximum pitch frequency.
std_pitch: The standard deviation of pitch frequency, measuring variability in pitch.
spectral_skew: The skewness of the spectral distribution, indicating asymmetry.
spectral_kurtosis: The kurtosis of the spectral distribution, indicating the peakiness of the spectrum.
energy_entropy: The entropy of the signal energy, representing its randomness.
log_energy: The logarithmic energy of the signal, a compressed representation of energy.
mfcc_1_mean to mfcc_13_mean: The mean of the first 13 Mel Frequency Cepstral Coefficients (MFCCs), representing the timbral characteristics of the audio.
mfcc_1_std to mfcc_13_std: The standard deviation of the first 13 MFCCs, indicating variability in timbral features.
label: The target variable indicating the gender male(1) or female(0).
https://news.1rj.ru/str/datasets1
help identifying male and female voice
Features:
The dataset includes the following extracted audio features:
mean_spectral_centroid: The average spectral centroid, representing the "center of mass" of the spectrum, indicating brightness.
std_spectral_centroid: The standard deviation of the spectral centroid, measuring variability in brightness.
mean_spectral_bandwidth: The average width of the spectrum, reflecting how spread out the frequencies are.
std_spectral_bandwidth: The standard deviation of spectral bandwidth, indicating variability in frequency spread.
mean_spectral_contrast: The average difference between peaks and valleys in the spectrum, indicating tonal contrast.
mean_spectral_flatness: The average flatness of the spectrum, measuring the noisiness of the signal.
mean_spectral_rolloff: The average frequency below which a specified percentage of the spectral energy resides, indicating sharpness.
zero_crossing_rate: The rate at which the signal crosses the zero amplitude axis, representing noisiness or percussiveness.
rms_energy: The root mean square energy of the signal, reflecting its loudness.
mean_pitch: The average pitch frequency of the audio.
min_pitch: The minimum pitch frequency.
max_pitch: The maximum pitch frequency.
std_pitch: The standard deviation of pitch frequency, measuring variability in pitch.
spectral_skew: The skewness of the spectral distribution, indicating asymmetry.
spectral_kurtosis: The kurtosis of the spectral distribution, indicating the peakiness of the spectrum.
energy_entropy: The entropy of the signal energy, representing its randomness.
log_energy: The logarithmic energy of the signal, a compressed representation of energy.
mfcc_1_mean to mfcc_13_mean: The mean of the first 13 Mel Frequency Cepstral Coefficients (MFCCs), representing the timbral characteristics of the audio.
mfcc_1_std to mfcc_13_std: The standard deviation of the first 13 MFCCs, indicating variability in timbral features.
label: The target variable indicating the gender male(1) or female(0).
https://news.1rj.ru/str/datasets1
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archive.zip
3.6 MB
Gender Recognition by Voice (processed)
#KaggleDatasets #DataScience #MachineLearning #DataAnalysis #DataVisualization #OpenData #DataCleaning #TextClassification #NLP #SentimentAnalysis #BigData #APIAutomation #DataLicensing #SocialMediaData #PythonIntegration #DataModeling #kaggle #ComputerVision #python #LLM #DeepLearning #Pytorch #HuggingFace #Dataset
https://news.1rj.ru/str/datasets1💎
#KaggleDatasets #DataScience #MachineLearning #DataAnalysis #DataVisualization #OpenData #DataCleaning #TextClassification #NLP #SentimentAnalysis #BigData #APIAutomation #DataLicensing #SocialMediaData #PythonIntegration #DataModeling #kaggle #ComputerVision #python #LLM #DeepLearning #Pytorch #HuggingFace #Dataset
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Lightening Strikes Dataset NOAA
2018 lightning strike data by National Oceanic and Atmospheric Administration
Dataset Denoscription: NOAA Lightning Strikes Dataset
The NOAA (National Oceanic and Atmospheric Administration) Lightning Strikes dataset provides insights into lightning activity over a given region or time period. This dataset is a product of NOAA's weather monitoring and storm tracking systems, offering valuable information for meteorologists, researchers, and disaster management authorities.
https://news.1rj.ru/str/datasets1
2018 lightning strike data by National Oceanic and Atmospheric Administration
Dataset Denoscription: NOAA Lightning Strikes Dataset
The NOAA (National Oceanic and Atmospheric Administration) Lightning Strikes dataset provides insights into lightning activity over a given region or time period. This dataset is a product of NOAA's weather monitoring and storm tracking systems, offering valuable information for meteorologists, researchers, and disaster management authorities.
https://news.1rj.ru/str/datasets1
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archive.zip
12.1 MB
Lightening Strikes Dataset NOAA
#KaggleDatasets #DataScience #MachineLearning #DataAnalysis #DataVisualization #OpenData #DataCleaning #TextClassification #NLP #SentimentAnalysis #BigData #APIAutomation #DataLicensing #SocialMediaData #PythonIntegration #DataModeling #kaggle #ComputerVision #python #LLM #DeepLearning #Pytorch #HuggingFace #Dataset
https://news.1rj.ru/str/datasets1
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amazon_review_full_csv.tgz
613.9 MB
Amazon reviews - Full
Abstract:
34,686,770 Amazon reviews from 6,643,669 users on 2,441,053 products, from the Stanford Network Analysis Project (SNAP). This full dataset contains 600,000 training samples and 130,000 testing samples in each class.
Abstract:
34,686,770 Amazon reviews from 6,643,669 users on 2,441,053 products, from the Stanford Network Analysis Project (SNAP). This full dataset contains 600,000 training samples and 130,000 testing samples in each class.
#KaggleDatasets #DataScience #MachineLearning #DataAnalysis #DataVisualization #OpenData #DataCleaning #TextClassification #NLP #SentimentAnalysis #BigData #APIAutomation #DataLicensing #SocialMediaData #PythonIntegration #DataModeling #kaggle #ComputerVision #python #LLM #DeepLearning #Pytorch #HuggingFace #Dataset
https://news.1rj.ru/str/datasets1
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