19,997 machine learning datasets
19,997 dataset results
Wireless-Intelligence is a database website provided for AI-based wireless communication research, in which each dataset consists of hundreds and thousands of channel samples in different forms. The data is available for free to researchers for non-commercial use.
The peer-reviewed publication for this dataset has been presented in the 2022 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), and can be accessed here: https://arxiv.org/abs/2205.02596. Please cite this when using the dataset.
This dataset provides full historical daily stock price for Alphabet. There are 2 types of share class for Alphabet: GOOG and GOOGL. The two classes have very similar share price. This dataset is for GOOGL. This dataset is provided by Finsheet, a world-class provider of Excel stock price and stock price Google Sheets. Sourcing data directly from Finnhub, a well-known financial data provider, Finsheet's data quality is unmatched and the same data is being used by financial institutions all around the world. That is why Finsheet is recognized by the faculty and students at Columbia University as a top platform to get Excel stock price and stock price Google Sheets. Long story short, when it comes to financial data in spreadsheets, Finsheet is your number one option.
This is the DCF template provided by ValueInvesting.io, a high performing value investing platform. Within this template, users also have access to other models such as Dividend Discount Model and Earnings Power Value. The focus of ValueInvesting.io is to provide accurate and reliable intrinsic value for all stocks globally using valuation models, especially DCF and WACC. Users have experience consistent return by following the valuation results recommended by ValueInvesting.io. Furthermore, users can also view and edit all model assumptions when exporting the model to Excel or Google Sheets. Those are the reason why they are listed in the number one position in the list of top 5 best stock research websites curated by students at Columbia University.
Overview The goal: using simulation data to train neural networks to estimate the pose of a rover's camera with respect to a known target object
This dataset is collected by Datacluster Labs. To download full dataset or to submit a request for your new data collection needs, please drop a mail to: sales@datacluster.ai This dataset is an extremely challenging set of over 9000+ original Trash/Garbage images captured and crowdsourced from over 2000+ urban and rural areas, where each image is manually reviewed and verified by computer vision professionals at ****DC Labs.
This dataset is collected by Datacluster Labs. To download full dataset or to submit a request for your new data collection needs, please drop a mail to: sales@datacluster.ai This dataset is an extremely challenging set of over 2000+ original Indian Traffic Sign images captured and crowdsourced from over 400+ urban and rural areas, where each image is manually reviewed and verified by computer vision professionals at DC Labs.
This dataset is collected by DataCluster Labs. To download full dataset or to submit a request for your new data collection needs, please drop a mail to: sales@datacluster.ai This dataset is an extremely challenging set of over 20,000+ original Number plate images captured and crowdsourced from over 700+ urban and rural areas, where each image is manually reviewed and verified by computer vision professionals at DC Labs.
This dataset is collected by DataCluster Labs. To download full dataset or to submit a request for your new data collection needs, please drop a mail to: sales@datacluster.ai This dataset is an extremely challenging set of over 50,000+ original Vehicle images captured and crowdsourced from over 1000+ urban and rural areas, where each image is manually reviewed and verified by computer vision professionals at Datacluster Labs.
The data originate from the journalistic domain in the Czech language. We describe the process of collecting and annotating the data in detail. The dataset contains 138,556 human annotations divided into train and test sets. In total, 485 journalism students participated in the creation process. To increase the reliability of the test set, we compute the annotation as an average of 9 individual annotations. We evaluate the quality of the dataset by measuring inter and intra annotation annotators' agreements. Beside agreement numbers, we provide detailed statistics of the collected dataset. We conclude our paper with a baseline experiment of building a system for predicting the semantic similarity of sentences. Due to the massive number of training annotations (116 956), the model can perform significantly better than an average annotator (0,92 versus 0,86 of Person's correlation coefficients).
This dataset is an extremely challenging set of over 20,000+ original Construction vehicle images captured and crowdsourced from over 600+ urban and rural areas, where each image is manually reviewed and verified by computer vision professionals at Datacluster Labs.
A dataset with $23\,870$ digital trajectories (i.e. time series) of handwritten lower- and uppercase Latin letters and Arabic numbers ($a$-$z$, $A$-$Z$, $0$-$9$), generated by $77$ experts using a Wacom Pen Tablet. An expert is considered a proficient user of the recorded symbols, in this case adult native German speakers.
Annotated and original images of billboards in Japanese street scapes
This dataset was created for Fongbe automatic speech recognition task and contains about 3979 recordings of 13 participants reading a text written in Fongbe, one sentence at a time. Fongbe is a vernacular language spoken mainly in Benin, by more than 50% of the population, and a littke in Togo and in Nigeria. It’s an under-resourced because it lacks linguistics resources (speech corpus and text data) and very few websites provide textual data. In this dataset, each example contains the audio files and the associated text. The audio is high-quality (16-bit, 16kHz) recorded using an adroid app that we built for the need. The dataset is multi-speaker, containing recordings from 13 volunteers (male and female).
The dataset consists of images of Human palms captured using a mobile phone. The images have been taken in a real-world scenario like holding objects or performing simple gestures. The dataset has a wide variety of variations like illumination, distances etc. It consists of images of 3 main gestures: Frontal-open palm, Back open palm and fist with the wrist. It also has a lot of images with people wearing gloves.
This dataset is an extremely challenging set of over 20,000+ original Number plate images captured and crowdsourced from over 700+ urban and rural areas, where each image is manually reviewed and verified by computer vision professionals at Datacluster Labs
This dataset consists of images of bottles and cups.
This dataset is an extremely challenging set of over 3000+ original Transparent object images such as glasses and mirrors are captured and crowdsourced from over 500+ urban and rural areas, where each image is manually reviewed and verified by computer vision professionals at Datacluster Labs.
This dataset is an extremely challenging set of over 3000+ originally Stair images captured and crowdsourced from over 500+ urban and rural areas, where each image is manually reviewed and verified by computer vision professionals at Datacluster Labs.
This dataset is an extremely challenging set of over 2000+ original Oximeter images captured and crowdsourced from over 300+ urban and rural areas, where each image is manually reviewed and verified by computer vision professionals at Datacluster Labs.